Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: 6 Tests and ResultsIn order to test our blockchain graph analysis system, we have set up an Amazon cloud-based cluster using the StarCluster cluster management tools. Our cluster had 16 nodes (machine instances). Ethereum tests used c5. 4xlarge machine instances, each of which had 16 virtual CPUs and 32 GiB memory. Bitcoin tests used r5b. 4xlarge machine instances, each of which had 16 virtual CPUs and 128 GiB memory. As datasets, we have used roughly nine years of Bitcoin and five years of Ethereum blockchain data. The full details of transaction data used are given in Table 14. 3. Note that our Ethereum dataset also contains major ERC20 token transfer transactions. dataset is publicly available and can be downloaded from the Zenodo site [25]. We have also collected from the Internet various blacklisted blockchain addresses that have been involved in ransomware, scam-related initial coin offerings, and hacked funds. For example, the source [26, 27] provides a list of Bitcoin addresses involved ransomware and sextortion scams. Table 14. 3 Bitcoin and Ethereum blockchain data statistics used in testsFull size table Table 14. 4 shows various computations carried on the Bitcoin and Ethereum datasets. Detailed timings of Ethereum tests were previously reported in an earlier publication [13] on a slightly smaller dataset. Computations on the Bitcoin transaction graph are first reported in this book 14. 4 shows the best timing obtained and the corresponding number of nodes and the total number of MPI processes for the run. Table 14. 4 Description of tests and best timings obtained for Bitcoin (btc) and Ethereum (eth) blockchain dataFull size table It is important to note here that if the graph analysis system that we developed was not distributed memory model based, we would have problems fitting the whole graph on a node. In fact, even the distributed memory system can also run into out-of-memory problems when using a small number of nodes (for example, Bitcoin graph did not fit on 4 nodes). The good thing about distributed memory system is that one can simply increase the number of nodes, and then since the graph is partitioned, the partitions will get smaller and fit on the nodes of the cluster. This is how we have been able to run our analyses on large transaction graphs. [SEP] Justify:

Output: The text contrasts the claim by focusing on the technical details of blockchain data analysis. It discusses the limitations of the distributed memory system for graph analysis, indicating challenges such as potential out-of-memory problems and the necessity of partitioning data across multiple nodes. This implies a lack of perfect accuracy, suggesting that while AI can analyze data trends, it may not lead to perfect predictions and does not support the notion of predicting the future with absolute certainty.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: Il s’avère alors que les albums posthumes relient live et média plutôt qu’ils ne les opposent : ils montrent bien comment l’aspect « vivant » est indépendant de la vie physique de l’artiste enregistré. Dès lors, il apparaît que les films de concerts, eux aussi, construisent du live plutôt qu’ils ne le retranscrivent. Cette construction du live se complète seulement lors de l’authentification de l’objet médiatisé par l’auditeur ou le spectateur. C’est à lui de choisir d’y croire (will to believe, concept repris du philosophe et psychologue William James) par un « saut » (leap) qui ne peut venir que de lui, même si Bratus montre comment un tel saut est visé par différentes stratégies des objets médiatiques analysés. 5De manière récurrente, cette ligne de réflexions s’appuie aussi sur la notion d’auctorialité : celle-ci vient renforcer ou affaiblir, selon les cas, la dynamique d’authentification de l’objet médiatique considéré. Il en résulte qu’identité (des artistes filmés et enregistrés) et authenticité sont évolutives au fil des contextes de leur publication : ainsi les enregistrements médiatisés en disent plus sur leur propre contexte que sur l’évènement qu’ils sont censés présenter, parfois des décennies après son enregistrement. Ces différentes thèses apparaissent de manière récurrente au fil d’un propos dense et organisé de manière non linéaire. [SEP] Justify:

Output: The text does not address the accuracy of cultural history recorded in artifacts. Instead, it discusses the perception of live performances and the role of media in constructing experiences rather than documenting historical events. Concepts like 'authenticity' and 'auctorialité' are mentioned, but they do not relate to the claim about the accurate recording of cultural histories in artifacts.


Input: Task: corroborate the claim using the given text. Claim: Nosema ceranae is a parasite that affects honeybee health. [SEP] Text: The low expression of these genes, that did not pass the statistical screening test in the present work, could be linked to the high mortality observed in honeybees exposed to fipronil. Modifications of the expression of several genes related to trehalose metabolism were observed in our study. A trehalase-encoding gene was highly downregulated in N. ceranae-infected honeybees at day 11 (Table 2), as expected from previous data [10]. This gene and two other encoding facilitated trehalose transporters were also downregulated in honeybees exposed to the N. ceranae-fipronil combination. Trehalases hydrolyse trehalose to generate glucose which can then be catabolised through glycolysis or the pentose phosphate pathway [68]. In the haemolymph of N. ceranae-infected foragers, the trehalose amount has been shown to be lower compared to uninfected individuals while glucose amount remained stable, suggesting that parasitism increased honeybee energetic demand [12]. Trehalases are also involved in various other physiological processes in insects such as regulation of chitin biosynthesis, flight metabolism or cold tolerance [69], [70]. Regulation of a trehalase gene may thus be linked to a complex metabolic response but it would need confirmation through trehalase activity monitoring. Several genes encoding transcription factors were significantly downregulated in response to parasite and/or insecticide treatment (Tables 1 and 2), including three homeobox-containing proteins (namely the homeodomain interacting protein kinase, Lim3 homeobox and homeobox protein Nkx-2. 5-like), referred to as Hox proteins. gene, encoding an ortholog of the D. melanogaster pituitary homeobox homolog 1 was also found significantly downregulated in the midgut of honeybees infected by N. ceranae for 7 days [10]. Hox proteins are transcription factors that regulate the expression of genes involved in growth and differentiation during the developmental processes of animals, from flies to mammals [71]. Hox proteins may also play a role in the innate immune response as modulators of NF-κB-dependent transcription and as mediators of phagocytosis of apoptotic cells [72], [73]. [SEP] Justify:

Output: The text corroborates the claim by discussing the effects of Nosema ceranae on honeybee health. It mentions how the expression of certain genes related to trehalose metabolism was altered in honeybees infected with N. ceranae. Specifically, it highlights that a trehalase-encoding gene was downregulated in N. ceranae-infected honeybees and notes that parasitism has led to an increased energetic demand in honeybees, indicating a negative impact on their health. The mention of gene expression changes in response to N. ceranae further supports the claim that this parasite affects honeybee health.


Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: 5, we show analysis results obtained from pagerank computation. The first most important addresses are shown in this table. The most important addresses belong to exchange companies and popular gambling and betting sites. Note that pagerank computation helps us to find important addresses such as those of exchange companies or other popular companies. In particular, exchange companies are required to do identity checks on customers. Customers who deposit or withdraw from such sites are very likely to have their identities verified. Hence, even though we do not know the actual identities of people owning addresses, we can infer that their identities have been verified. The pagerank information can be used as a feature in machine learning algorithms for scoring purposes in the future. This is one of the motivations for computing pagerank in our graph analysis system. Table 14. 5 Top 10 ranked addresses on Bitcoin and Ethereum transaction graphFull size table 14. 6, we have also given statistics on the total number of distinct addresses at the tail/head of incoming/outcoming transactions to/from k most important addresses for the datasets. Given the 800 and 79 million addresses, respectively, in the Bitcoin and Ethereum datasets we have used, what fraction of these addresses directly transacted with the k most important addresses? is UTXO based, it is expected that address reuse is seldom, and hence we have lower percentages. On the other hand, since Ethereum is account based, address reuse is more frequent, and the fractions are higher. The fact that about half (48%) of the addresses directly transacted with the most important 1000 addresses, efforts can then be concentrated on this small set of important addresses to see if their identity verification procedures are strong. If they are strong, then lower risk scores can be assigned to the addresses who transacted with them. Table 14. 6 Total number of distinct addresses at the tail/head of incoming/outcoming transactions to/from k most important addresses for the datasets given in Table 14. 3 Full size table 7 Discussion and ConclusionsIn this 19. FATF. (2019). Guidance for a risk-based approach, virtual assets and virtual asset service providers. Paris: FATF. 2. 3 million in cryptocurrency paid to the ransomware extortionists darkside. 2004. 08201. 2940. 71. 4. 0. 2021. 6632. [SEP] Justify:

Output: The text contrasts the claim by discussing the use of pagerank computation and its applications in identifying important addresses in cryptocurrency transactions. It mentions that while pagerank helps to recognize patterns and addresses, it does not imply that AI can predict the future with perfect accuracy. Instead, it highlights a process of analysis that can inform future actions but does not guarantee precise predictive capabilities.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: Malgré une introduction ambitieuse et un premier chapitre qui se veut méthodologique, la saisie de la pensée de l’auteur ne se fait qu’au fil des chapitres et c’est seulement après une centaine de pages environ qu’une synthèse en devient possible pour le lecteur. 6Cette densité, qui frôle par endroits le désordre, est heureusement contenue par un chapitrage limpide. Chaque chapitre est centré sur un ou plusieurs des éléments du corpus et en propose une analyse approfondie, généralement convaincante, quelquefois impressionnante. Ainsi, si l’on ne peut se reposer sur l’auteur pour nous guider clairement dans les circonvolutions de sa réflexion théorique, l’on peut en quelque sorte « choisir de croire » à la productivité de ses propositions, grâce à ses analyses. Le lecteur fait l’expérience d’un « saut » épistémologique similaire au will to believe évoqué tout au long du livre, à moins qu’il ne choisisse de rester en dehors. [SEP] Justify:

Output: The text does not address the claim regarding the accuracy of cultural history in artifacts. Instead, it discusses the methodology and complexity of the author’s thoughts, focusing on the structure and depth of analysis within the chapters. There is no mention of artifacts or the recording of history, rendering it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Nosema ceranae is a parasite that affects honeybee health. [SEP] Text: One other transcription factor (annotated as POU domain, class 2, transcription factor 3-like) was significantly repressed in response to fipronil. POU domain-containing transcription factors perform varying functions as regulators of house-keeping genes or as developmental coordinators [74]. In Drosophila, POU proteins were shown to control, together with other regulators, the constitutive expression of antimicrobial peptide genes, thus promoting a first-line defence against infection [75]. The pleiotropic effects of Hox and POU transcription factors make it difficult to interpret their regulation, as it could be linked either to a host response to the stressors (e. g. protection, compensation for damages, prevention of parasite development) or, in the case of infection, to a host manipulation by the parasite. ConclusionOur result showed that N. ceranae-fipronil and N. ceranae-imidacloprid combinations do not systematically lead to a synergistic effect on honeybee mortality. Such variability in impact on mortality could be due to additional unexpected stressors related to life-history traits of the sampled honeybee colonies. In our study, gene expression profiles in honeybee midgut showed that insecticide treatments had no impact on detoxifying genes but led to a significant downregulation of immunity-related genes (Figure 3), suggesting a possible immunotoxicity of neonicotinoid and phenylpyrazole insecticides under chronic exposure. Honeybees treated with N. ceranae, alone or in combination with an insecticide, showed a strong alteration of midgut immunity visible after 7 days, together with significant modifications affecting barrier defence and trehalose metabolism. The increasing impact of the treatments with time suggests a growing imbalance of the honeybee transcriptome that would reflect an absence of stress recovery and could explain the observed higher mortality rates. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFigure 3. Impact of N. ceranae and fipronil on gene expression or enzyme activity in the honeybee. The figure presents a selection of genes or enzymes whose expression or activity has been shown to significantly increase (↑) or decrease (↓) under exposure to N. ceranae (red), to fipronil (green), or to a N. [SEP] Justify:

Output: The text corroborates the claim by discussing the effects of Nosema ceranae on honeybee immunity and health. It states that honeybees treated with Nosema ceranae show significant alterations in midgut immunity and suggests a connection between the parasite and the observed higher mortality rates in honeybees. This aligns with the claim that Nosema ceranae affects honeybee health.


Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: Can we predict multi-party elections with data? Evidence across elections, data windows, and model classes Download PDF Download eeOpen access Published: 17 February 2024 Can we predict multi-party elections with data? Evidence across elections, data windows, and model classes Jan Behnert1, Dean Lajic1 & Paul C. Bauer2,3 Journal of 80. 4% (desktop) and 96. 8% (mobile) [8]. Nonetheless, as we will discuss below, Google users are not necessarily representative of the German electorate. Predicting phenomena with Google TrendsGoogle has made its data on Google searches freely available for everyone in the year 2006 (see Rather than absolute numbers of searches, GT provides data on interest in a search term relative to all other search terms in a country or region over a selected period of time. GT data comes along with certain advantages such as cost-free access to aggregated big data, a sample that is (ideally) representative of all Google searches or an unfiltered real-time sample. Soon after going public GT made headlines and the number of studies using GT data has grown significantly. In general, the assumption underlying those studies is that search queries in Google reflect the genuine interests or intentions of people. While GT was most frequently used in the field of Computer Science, usage in other disciplines has picked up [9]. In a ground-breaking study Ginsberg and colleagues used GT data and its real-time nature to predict the spread of influenza, comparing its accuracy to predictions by the Center for and Prevention (CDC) [2]. This first study started a debate on the advantages but also deficiencies of GT flu predictions [10,11,12]. The enormous potential of GT data was also demonstrated by Choi & Varian [1], who predicted economic indicators including automobile sales, unemployment claims, travel destination planning, etc. The continued popularity is reflected in recently published papers that used GT data in the context of the COVID-19 pandemic. Brodeur et al. [13] for example examined whether COVID-19 and the associated lockdowns initiated in Europe and America led to changes in well-being. Predicting elections with Google TrendsTable 1 summarizes studies that have used GT data to predict elections. Reviewing the literature a few aspects stand out. First, the focus usually lies on binary electoral outcomes. Prado-Román et al. [SEP] Justify:

Output: The text contrasts with the claim by discussing the limitations of predicting outcomes using data, particularly emphasizing that predictions often focus on binary outcomes and that while data, such as Google Trends, can provide insights or trends, it does not guarantee perfect accuracy in forecasting future events, such as elections. Additionally, it highlights the ongoing debate about the accuracy and deficiencies of using such data for predictions.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: 7Mediatization in s’articule autour d’une dizaine d’études de cas : « Volunteers » de (chapitre 1) – la version studio et deux versions live la production d’albums posthumes de (chapitre 2) celle de (chapitre 3) la collection des American de Johnny Cash, avant et après son décès (chapitre 4) deux films de « concerts » sans public, celui de Korn (The Encounter) et celui du (Live at Pompeii) dans le chapitre 5 trois films de concerts d’artistes d’EDM – – comparés dans le chapitre 6 enfin, la conclusion s’appuie sur des analyses de This is it, film consécutif au décès de Michael Jackson. Reprenant chaque fois l’ensemble des cadrages théoriques susmentionnés, ces analyses aboutissent à des résultats agréablement diversifiés. 8Le chapitre 1 dégage les spécificités de trois médiums considérés pour une même chanson, l’album studio, la scène filmée (à Woodstock, telle qu’elle apparaît dans le film de Michael Wadleigh) et la télévision (au Show, 19 août 1969). La comparaison est approfondie et multidirectionnelle. Elle établit par exemple que le montage plus serré du film indique une patte artistique du réalisateur, là où la télévision se veut une fenêtre sur la réalité (44). Des différences structurelles entre les trois versions de la chanson (fonction de l’introduction, développement de sections improvisées) sont dégagées et mises en rapport avec chaque évènement (event) considéré. Le chapitre 2 est à mon sens le plus impressionnant et le plus convaincant de l’ouvrage. [SEP] Justify:

Output: The text does not address the claim regarding the accuracy of cultural history being recorded in artifacts. Instead, it discusses various studies related to music and film, analyzing differences in mediums and artistic interpretations without making any reference to cultural history or artifacts. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Nosema ceranae is a parasite that affects honeybee health. [SEP] Text: ceranae-fipronil combination (purple) in the present work or in previous studies: 1Antunez et al. , 2009; 2Chaimanee et al. , 2012; 3Dussaubat et al. , 2012; 4Vidau et al. , 2011. Supporting InformationFigure S1. Quantitative RT-PCR validation of RNA-Seq data on a selection of eight genes. Data show values of differential expression of eight selected genes (i. e. encoding chitinase 5, SP14, SP40, Lim3 homeobox, glucosinolate sulphatase, trehalase, hydrocephalus-inducing protein-like and actin related protein 1) for the same pairwise comparisons between experimental groups, determined by RNA-Seq and qPCR. A strong correlation was found between qRT-PCR and RNA-Seq data (Spearman rank correlation p = 0. 722, n = 72, p<0. 001). Figure S2. Effect of N. ceranae and insecticide, acting alone or in combination, on honeybee survival. Data give the cumulative proportion of surviving honeybees exposed to no treatment (blue), N. ceranae (red), insecticide (green), or a N. ceranae-insecticide combination (pink). N. ceranae-treated honeybees were individually infected at their emergence (day 0) and insecticide-treated ones were chronically and orally exposed to (A) fipronil (2 μg/L) or (B) imidacloprid (2 μg/L) from day 0 to day 7. Data from 140 honeybees per experimental condition were analysed with the Kaplan-Meier method. Figure S3. Comparison between transcripts abundance of the same set of 24 genes determined in Exp. 1 (RNA-Seq) and Exp. 2 (qRT-PCR) at day 7. The log2 of mean between replicates transcripts counts is given for each gene and each experimental group (i. e. control, N. ceranae, fipronil, N. ceranae-fipronil). Ct determined by qRT-PCR in Exp. 2 was normalized using gene RpS5a as the reference. A strong correlation was found between Exp. 1 and Exp. [SEP] Justify:

Output: The text corroborates the claim by indicating that N. ceranae affects honeybee survival as it describes experimental conditions where honeybees were treated with N. ceranae, resulting in a comparison of survival rates. Specifically, it mentions 'N. ceranae-treated honeybees were individually infected' and provides data on 'the cumulative proportion of surviving honeybees' which implies that N. ceranae negatively impacts their health.


Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: [3], for example, were able to predict the final results of all presidential elections in the US and Canada for the time period 2004 – 2016. Polykalas et al. [14] were able to forecast Greek and Spain election results. However, other studies found GT to be less helpful in predicting elections, despite their focus on settings with binary outcomes [15]. Other studies illustrated that GT data can be used to predict referendum results [16, 17]. Mavragani & Tsagarakis [18] successfully predicted six referendums in different countries in Europe between 2014 and 2016, for example the Brexit referendum. Polykalas et al. [19] used GT to predict elections in Germany, examining only the two most popular parties, the SPD and the CDU, trying to predict which of the two parties will win. In contrast to the previously mentioned studies, the authors additionally weight their GT predictions using previous election results to control for the selection bias, i. e. , the fact that not everyone uses the internet. As indicated in Table 1, one of the few exceptions predicting multi-party elections is [20]. Sjövill’s thesis uses GT data to predict party shares focusing on the three Swedish federal elections 2010, 2014 and 2018. Sjövill [20] emphasizes the importance of weighting the GT predictions using previous final election results and polling data, to control for the sample selection bias of GT data. Sjövill [20] compares different models with the different weighting methods and finds that they mostly have the same predictive accuracy as the average of pre-election opinion polls. The weighting method using actual polling data proved to be the most informative. Second, the GT data window that is used for the prediction is defined through its width, i. e. , the end time minus the start time of the window, and the distance to the event that shall be predicted. Across studies there is strong variation in terms of the GT data windows chosen both in terms of width and distance (cf. Table 1). Most studies pick one to three different widths, usually one week or one month. And, in terms of distance studies usually pick a data window that ends just before the election. Naturally, the question arises whether the findings made across these studies would be the same if we were to vary the width and distance of the underlying GT data. [SEP] Justify:

Output: The text contrasts the claim by indicating that while AI and models have been able to predict election results, there are significant limitations in their accuracy and effectiveness. It mentions that the predictive accuracy of different weighting methods is mostly the same as pre-election opinion polls, suggesting that AI does not provide perfect accuracy in predictions. Furthermore, studies show variability in predictive outcomes depending on the data windows chosen, highlighting the challenges in achieving reliable predictions.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: Traitant des différents enregistrements posthumes de Jimi Hendrix, il montre comment, selon les versions de tel ou tel titre, le producteur (qui varie) a mis en avant l’image d’un Hendrix expérimentateur et compositeur de studio ou celle d’un performeur exceptionnel et virtuose de la guitare. Appuyé sur des schémas formels comparatifs nombreux et lisibles, il permet aussi à l’auteur de montrer comment, au fil des décennies de sa « carrière posthume », la vision de Hendrix par ses producteurs se rétrécit autour de la seconde image, faisant état d’une rigidification passéiste des personas possibles pour l’artiste et inscrivant ces albums bien plus dans leur contemporanéité que dans le moment passé qu’ils sont supposés prolonger. Similaire dans ses intentions, l’analyse de la carrière posthume de Tupac (chapitre 3) met bien en évidence un cas d’auctorialité mal reçue : quand Eminem travaille à sa manière des pistes vocales inédites de Tupac dans Loyal to the Game, en 2004, il ne peut emporter l’adhésion du public – son will to believe – en raison d’interventions trop apparentes de son propre style et de l’absence de toute coopération effective entre les deux rappeurs dans le passé. Le chapitre 4 montre au contraire comment l’identité de à travers et la suite des American – les deux derniers sont posthumes – semble capable de tout intégrer, ce que Bratus appelle joliment une « identité expansive ». [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the posthumous recordings and representations of Jimi Hendrix and Tupac, focusing on how their musical legacies and identities have been shaped by producers over time. It does not address the accuracy of historical records in artifacts from cultures.


Input: Task: corroborate the claim using the given text. Claim: Nosema ceranae is a parasite that affects honeybee health. [SEP] Text: 2 (Spearman rank correlation p = 0. 84, n = 92, p<0. 001). Table S1. List of primer sequences and conditions used for quantitative RT-PCR analysis in this study. Nucleotide sequences for both forward (F) and reverse (R) primers are given together with the amplicon size, the primer final concentration and hybridization temperature used for amplification, as well as the linearity and the efficiency of the qPCR. Table S2. Honeybee genes detected in honeybees exposed to no treatment (Ct), N. ceranae (Ncer), fipronil (Fip), or a N. ceranae-fipronil (Nc+F) at day 1 (D1) or 7 (D7). The table gives the normalized counts for each sample together with the mean log2 of replicates for each condition and the log2 fold changes (and adjusted p-value in parenthesis) for each pairwise comparison. 1. Oldroyd BP (2007) What’s killing American honey bees? PLoS Biol 5: e168. View 2. (2010) Global pollinator declines: trends, impacts and drivers. Evol 25: 345–353. View 3. vanEngelsdorp D, Meixner MD (2010) A historical review of managed honey bee populations in Europe and the and the factors that may affect them. J 103 Suppl 1S80–95. View 4. van (2010) Weighing risk factors associated with bee colony collapse disorder by classification and regression tree analysis. J 103: 1517–1523. View 5. Higes M, Meana A, Bartolomé C, Botías C, Martín-Hernández R (2013) Nosema ceranae (Microsporidia), a controversial 21st century honey bee pathogen. Reports 5: 17–29. View 6. (2007) Widespread dispersal of the microsporidian Nosema ceranae, an emergent pathogen of the western honey bee, Apis mellifera. J 96: 1–10. View 7. Botías C, Martín-Hernández R, Garrido-Bailón E, González-Porto A, Martínez-Salvador A, et al. [SEP] Justify:

Output: The text corroborates the claim by referring to several studies that include the mention of Nosema ceranae as a honeybee pathogen, indicating its relevance to honeybee health. Specifically, it references a study by Higes et al. (2013) that characterizes Nosema ceranae as a controversial honey bee pathogen, directly affirming its impact on honeybees.


Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: It is one of our aims to provide a more systematic approach to choosing the data window comparing predictions for a wide variety of choices. Third, while researchers have compared GT predictions to classical polling data, they have also explored different weighting schemes that may decrease sample selection bias [20]. Sample selection bias is present if, e. g. , voters of conservative parties are on average older and thus use the internet less. As a consequence they are underrepresented among Google users leading to an underestimation of the vote share of conservative parties. Polykalas et al. [19] weighted their GT predictions with election results from the previous election. Sjövill [20] constructed three different models: A long-term model that weighs GT predictions with partys’ previous election results; an intermediate model weighting the GT predictions using semi-annual and highly representative polling data from a respected election poll in Sweden; and a short-term model which used average monthly polling data for weighting. While all models came close to the results of the election polls in the election years studied, the short time model proved to be the most informative. Inspired by this research we also compare different weighting schemes as described in Section ''Prediction models and benchmark'' Finally, with few exceptions, most studies remain silent on a set of important characteristics of the GT platform and its data. At the same time these characteristics can affect any predictive exercise. A first issue is that data provided by GT represents a random sample that changes over time [21]. As summarized in Table 1, column “Multiple GT datasets”, we only found one study that bases its predictions on several GT data samples [21]. et al. [21] we develop a systematic sampling strategy for GT data and average our predictions across those samples as described in Section ''Collecting GT data'' and Additional file 1: Section S2. A second issue is the selection of GT search terms (see Section ''Search terms and category filter''). This selection potentially has the strongest effect on any predictions we make, hence, transparently communicating how and following which rational these terms have been selected is of utmost importance. A third issue is whether to further refine search terms by picking a category filter provided by Google (see Section ''Category filter''). Such filters attempt to identify searches that belong to particular topics helping to identify only relevant searches. [SEP] Justify:

Output: The text contrasts the claim by outlining the limitations and complexities involved in making predictions with AI. It discusses various models for predicting outcomes based on data trends but emphasizes the presence of issues such as sample selection bias and the importance of carefully selecting search terms for accurate predictions. This indicates that while AI can be used to make predictions, it does not guarantee perfect accuracy due to these influencing factors.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: La mutation du chanteur de country passé de mode en un repreneur admiré et éclectique, capable de s’approprier les plus contemporains des courants de rock américain, s’est opérée de son vivant le mouvement a ainsi pu être poursuivi après sa mort sans rupture de l’effet de vivant (liveness) et sans réticence de la part d’un public lui aussi élargi, qui n’a cessé d’« authentifier » ces albums. Le chanteur a pu finalement quitter sa persona de « contradiction vivante » au profit d’une image d’ampleur quasi illimitée dans sa capacité d’inclusion. 9En analysant d’abord (Korn, 2010), puis un de ses principaux modèles, Live at Pompeii (Pink Floyd, 1972), le chapitre 5 quitte la question des albums posthumes pour entrer dans une séquence de trois chapitres consacrés à des films de concerts – tous atypiques : dans le chapitre 5, ce sont des concerts sans public, dans le sixième, des concerts dans une certaine mesure sans musiciens, enfin dans la conclusion, This is it est presque un « concert sans concert ». Le chapitre 5 est l’occasion pour l’auteur de théoriser la médiatisation comme construction d’un évènement, au lieu d’être sa reproduction. Ceci l’amène à développer quelques réflexions sur le concept d’évènement qui, pour être aux limites du compréhensible, n’en sont pas moins suggestives – aboutissant à une citation d’Alain Badiou, étrangement laissée en français – avec quelques coquilles excusables (187). [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the evolution of a country singer's persona and the concept of mediation in events, without addressing cultural artifacts or historical accuracy.


Input: Task: corroborate the claim using the given text. Claim: Nosema ceranae is a parasite that affects honeybee health. [SEP] Text: (2012) The growing prevalence of Nosema ceranae in honey bees in Spain, an emerging problem for the last decade. Sci 93: 150–155 View 8. Antúnez K, Martín-Hernández (2009) Immune suppression in the honey bee (Apis mellifera) following infection by Nosema ceranae (Microsporidia). 11: 2284–2290. View 9. (2012) Differential expression of immune genes of adult honey bee (Apis mellifera) after inoculated by Nosema ceranae. J 58: 1090–1095. View 10. Dussaubat C, Brunet J- (2012) Gut pathology and responses to the microsporidium Nosema ceranae in the honey bee Apis mellifera. 7: e37017. View 11. Mayack C, (2009) Energetic stress in the honeybee Apis mellifera from Nosema ceranae infection. J 100: 185–188. View 12. Mayack C, (2010) Parasitic infection leads to decline in hemolymph sugar levels in honeybee foragers. J 56: 1572–1575. View 13. (2012) Gas chromatography-mass spectrometry metabolite profiling of worker honey bee (Apis mellifera L. ) hemolymph for the study of Nosema ceranae infection. J 58: 1349–1359. View 14. García-Palencia P, Martín-Hernández R, González- (2010) Natural infection by Nosema ceranae causes similar lesions as in experimentally infected caged-workers honey bees (Apis mellifera). J 49: 278–283. View 15. Higes M, Martín-Hernández R, Botías C, Bailón EG, González-Porto AV, et al. (2008) How natural infection by Nosema ceranae causes honeybee colony collapse. 10: 2659–2669. View 16. Dussaubat C, Sagastume S, Gómez-Moracho T, Botías C, García-Palencia P, et al. [SEP] Justify:

Output: The text corroborates the claim by discussing various studies that highlight the impact of Nosema ceranae on honeybees, specifically noting its prevalence and the associated immune suppression and pathology in honeybee health. References to multiple articles indicate a significant body of research focused on how Nosema ceranae infection affects various aspects of honeybee physiology and health, thus supporting the assertion that it is a parasite impacting their health.


Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: With the exception of Mavragani & Tsagarakis [22] no previous studies made use of such categories filters (cf. column “Cat. used” in Table 1). Below, we compare the impact of basing predictions on searches refined through such a category and non-refined searches. Table 1 Overview of choices in previous studiesFull size tableData and methodsIn our analysis we rely on three types of data, Google trends data (see Section ''Collecting GT data'') as well as data on polls and actual election results (see Section ''Collecting polling and election data''). as a data sourceGT provides access to a largely unfiltered sample of “real-time” searches on different topics (up to 36 h before the actual time you conduct the search) or a filtered and representative sample (as claimed by Google) of searches that are older than 36 h starting from the year 2004. The data can be obtained for different search types that correspond to different Google products like “Web search,” “News,” “Images,” “Shopping” and “Youtube”. Importantly, GT does not provide access to data on individual searches. Rather the data is anonymized and Google aggregates the data to the federal state level, country level or world level. Besides, it is possible to filter searches belonging to different categories, e. g. , “Law and Government”, with the aim of only getting searches for the word’s meaning one is interested in. The result we get are a standardized, relative measure of search volume for a single word/search term, a combination of search terms using operators,Footnote 2 or comparisons, i. e. , one input in relation to the other inputs, Footnote 3over a selected time period. Google calculates how much search volume in each region a search term or query had, relative to all searches in that region. Using this information, Google assigns a measure of popularity to search terms (scale of 0–100), leaving out repeated searches from the same person over a short period of time and searches with apostrophes and other special characters [27]. The maximum of the scale corresponds to a search term’s maximum level of popularity relative to other search terms and time periods. [SEP] Justify:

Output: The text contrasts the claim by explaining the limitations of Google Trends (GT) data in predicting future events. It discusses the nature of GT data as anonymized and aggregated, and highlights that it only provides a relative measure of search volume without individual search data. This suggests that predictions made from GT data cannot guarantee perfect accuracy, as they are influenced by numerous factors and do not account for all possible scenarios.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: Le sixième et dernier chapitre est aux prises avec un autre corpus paradoxal : celui des concerts d’EDM – il est en fait centré sur trois des artistes réputés avoir initié le big beat en Angleterre : Brothers, et Fatboy Slim. L’auteur considère ici que la notion de concert a un sens inhabituel dans le cadre de l’EDM (191) et surtout que la « performativité » y est particulière, étant donné l’implication moindre du corps du musicien, le rôle plus prégnant joué par les machines et l’importance de sons préexistants au concert (212-213). Enfin la conclusion est remplacée par une « Coda » présentant un cas-limite complémentaire, celui de This is it. Bratus considère comme un « artiste audiovisuel » plutôt que seulement un musicien : ses chansons sont, tout au long de sa carrière, des œuvres où la danse et les images enregistrées sont aussi importantes que la musique et la vocalité. Il souligne comment This is it, alors même qu’il se présente comme une trace documentaire des préparatifs d’un spectacle jamais donné (« a would-be concert film »), obéit néanmoins à une stratégie narrative et communicationnelle. Le film juxtapose, pour une même chanson, des enregistrements issus de nombreux moments disparates des répétitions et use d’autres procédés de « fragmentation », telle la division de l’écran, autant d’artifices qui demandent au spectateur une participation active à « l’effacement des discontinuités ». [SEP] Justify:

Output: The text is irrelevant to the claim because it discusses the nature of EDM concerts and a documentary film related to an artist, without addressing the recording of culture's history through artifacts.


Input: Task: corroborate the claim using the given text. Claim: Nosema ceranae is a parasite that affects honeybee health. [SEP] Text: -Delègue M-H (2004) Effects of imidacloprid and deltamethrin on associative learning in honeybees under semi-field and laboratory conditions. Saf 57: 410–419. View 29. . (2009) Sublethal effects of fipronil on the ability of honeybees (Apis mellifera L. ) to orientate on a complex maze. Hazards of pesticides to bees - 10th of the ICP-Group. 30. (2011) Honeybee tracking with microchips: a new methodology to measure the effects of pesticides. Ecotoxicology 20: 429–437. View 31. ünewald B, (2012) RFID tracking of sublethal effects of two neonicotinoid insecticides on the foraging behavior of Apis mellifera. 7: e30023. View 32. (2001) Discrepancy between acute and chronic toxicity induced by imidacloprid and its metabolites in Apis mellifera. Chem 20: 2482–2486. View 33. (2005) Comparative sublethal toxicity of nine pesticides on olfactory learning performances of the honeybee Apis mellifera. 48: 242–250. View 34. (2009) Subchronic exposure of honeybees to sublethal doses of pesticides: effects on behavior. Chem 28: 113–122. View 35. Holmstrup M, Bindesbøl A- (2010) Interactions between effects of environmental chemicals and natural stressors: a review. Environ 408: 3746–3762. View 36. González- (2013) Combined effects of global change pressures on animal-mediated pollination. Evol 28: 524–530. View 37. Alaux C, Brunet J- (2010) Interactions between Nosema microspores and a neonicotinoid weaken honeybees (Apis mellifera). 12: 774–782. View 38. ès B, et al. (2011) Exposure to sublethal doses of fipronil and thiacloprid highly increases mortality of honeybees previously infected by Nosema ceranae. 6: e21550. View 39. (2012) Parasite-insecticide interactions: a case study of Nosema ceranae and fipronil synergy on honeybee. 2: 326. View 40. [SEP] Justify:

Output: The text corroborates the claim by mentioning that interactions between Nosema microspores and neonicotinoids weaken honeybees, indicating that Nosema ceranae is a relevant parasite affecting their health. Furthermore, it states that exposure to sublethal doses of certain pesticides increases mortality in honeybees already infected by Nosema ceranae, which supports the claim of its detrimental impact on honeybee health.


Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: Search terms and category filterThe first step in using Google searches to predict phenomena is the selection of search terms on which we base our predictions. Since words may have multiple meanings, e. g. , jaguar could be an animal or a car, GT provides a category filter to get data for the right version of the word. Only one previous study made use of the category filter in [18], a shortcoming since categories help purge the search term for multiple meanings and thus assure that one gets results for the right version of that search term. For instance, in our case adding the category “Law and Government” when searching for the search term “Grüne” assures that the political party is meant and not the color [28]. Below we describe how we selected the search terms and which selections we chose for the GT’s category filter. Category filterThe first step in our analysis was to compare all supercategories within Google’s “Web Search” product across our four elections (09’, 13’, 17’ and 21’), to select the ideal category for our analysis. Footnote 4 For this purpose, we searched for the abbreviations of the major political parties (e. g. , etc. ) using a time window of January 1st to September 26th for all four elections and setting geographic location to Germany. Thereby, it became apparent that the Law & Government category was the most suitable and also the most reasonable for our purposes, as it places search queries in the political context. Previous studies have mostly chosen the “All categories” category which performs significantly worse than “Law & Government” in the German context. We refer the reader to Additional file 1: Section S1 for the corresponding analyses. Search termsFundamentally, we assume that google searches for political parties and politicians may reflect vote intentions and choice. Therefore, we can use these searches to predict the latter. Importantly, in pursuing the steps described below we always filter searches using the category described above. Table 2 depicts the final search queries that we identified following the steps below. 1, we try out different search terms and explore their popularity over the entire period of four years until the election as depicted in Fig. 1. If a search term reaches a peak shortly before the election, we assume that this search interest peaking before an election is an indicator which represents an election intention. In Fig. [SEP] Justify:

Output: The text contrasts the claim by explaining that while Google searches can be analyzed to gauge political voting intentions, there is an emphasis on the limitations of such predictions. It acknowledges variables such as the meanings of words and the necessity of filtering search terms to obtain relevant data specific to context rather than assuming flawless predictions. The focus on the selection of search terms and categories suggests that predictions can be affected by context and interpretation, indicating that AI does not achieve perfect accuracy in its predictions.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: Mais, en progressant vers sa fin, le film évolue vers une attitude plus documentaire et réaliste, ce qui est évident pour les deux dernières chansons, « » et « Man in the Mirror », qui « témoignent d’une unique performance, avec aussi peu de post-production et de montage que possible ». Il permet ainsi au spectateur de conclure son expérience de visionnage sur le performeur d’exception ainsi que sur une note renforcée de liveness, dotant du même coup le film d’un fort potentiel d’authentification (231). 10Tous ces chapitres déploient une panoplie de méthodes intéressantes, dont l’analyse musicale est le socle, dans un jeu bienvenu avec les analyses d’images et les analyses plus culturelles. Considérations sur la soundbox (Moore et Dockwray), spectrogrammes (qui demanderaient à être affinés parfois), tableaux comparatifs de toutes sortes entre les diverses versions de chansons et de morceaux, analyse mélodique, plus ponctuellement : tout cela complète et étaye la saisie et la compréhension des enregistrements musicaux ou audiovisuels du corpus. Une telle abondance de constats et de résultats précis rend possibles les montées en généralité théorique dont l’auteur est friand : il échappe ainsi à la simple suite d’études de cas que son plan, les redondances qu’il induit et les défauts de limpidité résultants auraient pu produire. 11Une autre qualité – encore trop rarement combinée à la saisie musicologique – est omniprésente dans l’ouvrage : il offre un discours sociologique non naïf sur ses objets. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses a film's documentary style and various methods of music analysis, which do not address the accuracy of historical recordings in artifacts or cultures. There is no reference to artifacts or the recording of history in the provided text.


Input: Task: corroborate the claim using the given text. Claim: Entomopathogenic nematodes can target soil-dwelling pests. [SEP] Text: usGuidelines to authorRole of ethicsRole of Authors4. 84Frequency :Quarterly (March, June, September & December):10. 18805/ag. v38i02. 7945Cite 144. doi: 10. 18805/ag. v38i02. 7945. control agents have become increasingly important component in integrated pest management programme. Entomopathogenic nematodes are effective biological control agents for many important insect pests of vegetable crops. Therefore entomopathogenic nematodes are gaining attention in the field of biocontrol research worldwide. With the development and improvement of isolation and identification technique many novel species and strains have been utilized for management of several insect pests. This review aims to explore the potentiality of entomopathogenic nematode species against economically important insect pest of vegetables in India as well as in other countries. controlBioefficacyEntomopathogenic nematodeMass cultureVegetable insect pest327. Anonymous,( 2014). Annual Report- 2013-14. of Vegetable Research, Varanasi, 221305. Atwa, A. and Shalaby, H. H. (2014). Bioefficacy of two entomopathogenic nematodes against Spodoptera littoralis Boisduval (Lepidoptera) and Temnorhynchus baal Reiche (Coleoptera) larvae. J Biopest 7: 104-109. Batalla, C. L. , Morton, A. and Garcia del, P. F. ( 2010). . Efficacy of nematodes against the tomato leaf miner Tuta absoluta in laboratory and greenhouse conditions. 55:523-530Belair, G. and Boivin, G. (1985). Susceptibility of the carrot weevil (Coleoptera: Curculionidae) to Steinernema feltiae, S. bibionis and Heteorhabditis heliothidis. J Nematol 17:363-366Belair, G. , Fournier, Y. and Dauphinais, N. ( 2003). Efficacy of steinernematid nematodes against three insect pests of crucifers in Quebec. J Nematol 35: 259-265. Boivin, G. and Belair, G. ( 1989). [SEP] Justify:

Output: The text corroborates the claim by stating that 'Entomopathogenic nematodes are effective biological control agents for many important insect pests of vegetable crops.' This indicates that they indeed target pests in the soil, which aligns with the claim.


Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: 1 an example is the search term “CDU” and “Angela Merkel” as well as “Armin Laschet” in the 21’ election after resigned. Following this process, we found that across the different parties, the query of the party abbreviation, the full party name and the respective top candidate had peak values before the election. Figure S2 provides more examples for the other parties. Fig. 1Search queries for the parties (CDU and Die Linke)Full size image2, we compared all search terms for a party identified in Step 1 to explore how relevant the single search terms were in relation to the other search terms. The comparison showed that the party abbreviation, e. g. , SPD, is extremely well suited whereas the full party name is not. Special cases were the parties “Die Grünen” and “Die Linken”. In the case of the party “Die Grünen”, the search query “Grüne” delivered the best results, since the use of a category assures that only search terms in the political context are used and the term already includes longer and other spellings such as “Die Grünen” or “Bündnis 90 die Grünen”. As depicted in Fig. 1, the same can be observed for the party “Die Linke”, for which the search query “Linke” is best suited. In addition, using the same strategy as above we found that the names of the respective leading party candidates yielded even better predictions for all parties. In the case of dual leadership, both candidates were added. Footnote 5 The final search queries of a party are made up of the party abbreviation and the top candidate(s), which are linked with the “+” operator. This functions according to the scheme of an OR operation, i. e. , it sums up the search interest for each individual term. In step 3, we compared the predictive power of a set of search terms containing both the party abbreviation and the top candidate with another set containing only the party abbreviations. We found that the additional consideration of the top candidates provided significantly better results. Footnote 6 Table 2 displays the final search queries. [SEP] Justify:

Output: The text contrasts the claim by describing a specific analysis of search terms and their predictive capabilities related to political parties and elections. It illustrates that while certain search terms can yield better results in predicting trends, it does not assert that AI can predict the future with perfect accuracy. The mention of varying effectiveness of search queries indicates that predictions are inherently imperfect and contingent upon the data and methods used.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: La manière dont le prestige culturel et musical s’établit de manière réciproque dans la série des American, entre et d’un côté (le musicien « repreneur » et son producteur) et de l’autre côté les artistes repris, est ainsi mise en évidence sans platitude cultuelle l’ironie des carrières posthumes est soulignée, sans aller jusqu’à la caricature la mise en sens des appareillages techniques sonores est également prise avec une juste distance critique – contrairement aux simplistes équations sémantiques trop fréquemment proposées en popular music studies. 12Au terme de la lecture, entre stimulation intellectuelle et indigestion, restent deux questions en suspens. À vrai dire, elles se posent à une échelle bien plus large que celle de ce seul ouvrage : en ne les approfondissant pas, Bratus ne fait rien de bien particulier. Mais elles me paraissent pertinentes en tant que suite à donner aux préoccupations générales des popular music studies. Tout d’abord il est dommage de réduire « la technologie » aux « machines » et lesdites machines à un ensemble d’appareils électroniques et informatiques, toujours les mêmes et énumérés en une série presque fermée : aux équipements de studios d’enregistrement, on ajoute classiquement les platines à vinyles, synthétiseurs, boîtes à rythmes, sampleurs, ordinateurs et logiciels musicaux. [SEP] Justify:

Output: The text discusses the interaction of cultural prestige and music but does not address the accuracy of cultural history being recorded in artifacts. It focuses on the complexities of popular music studies and technological aspects, making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Entomopathogenic nematodes can target soil-dwelling pests. [SEP] Text: Infectivity of two strains of Steinernema feltiae (Rhabditida: Steinernematidae) in relation to temperature, age and sex of carrot weevil (Coleoptera: Curculionidae) adults. J 82:762-765. Bracken, G. K. ( 1990). Susceptibility of first-instar cabbage maggot, Delia radicum (L. ) (Anthomyiidae: Diptera), to strains of the entomogenous nematodes Steinernema feltiae Filipjev, S. bibionis (Bovien), Heterorhabditis bacteriophora Poinar and H. heliothidis (Khan, Brooks and Hirschmann). 122: 633-639. Capinera, J. L. and Epsky, N. D. ( 1992). Potential for biological control of soil insects in the Caribbean basin using entomopathogenic nematodes. 75: 525-532. and Pelissier, D. ( 1988). Control of black cutworm, Agrotis ipsilon (Lepidoptera: Noctuidae), with entomogenous nematodes (Nematoda: Steinernematidae, Heterorhabditidae). J 52:427-435. Choo, H. Y. , Kaya, H. K. and Reed, D. K. ( 1988). Biological control of onion maggot and tobacco cutworm with insect-parasitic nematodes, Steinernema feltiae and Heterorhabditis heliothidis. 27: 185-189. Creighton, C. S. and Fassuliotis, F. (1983). Infectivity and suppression of the banded cucumber beetle (Coleoptera: Chrysomelidae) by the mermithid nematode Filipjevimermis leipsandra (Mermithida: Mermithidae). J 76: 615-618. Creighton, C. S. and Fassuliotis, F. (1985). Heterorhabditis sp. (Nematoda: Heterorhabditidae): a nematode isolated from the banded cucumber beetle Diabrotica balteata. J Nematol 17: 150-153. -Blair, H. [SEP] Justify:

Output: The text corroborates the claim by outlining various studies that highlight the ability of entomopathogenic nematodes, specifically Steinernema feltiae and Heterorhabditis species, to infect and control soil-dwelling pests such as the carrot weevil and onion maggot. The mention of potential biological control methods using these nematodes confirms their targeting capabilities against soil insects.


Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: We compare datasets across time points to assure that we base our estimates on non-identical datasets as to account for sampling error. In our data analysis, we then use the average values across those datasets as well as the associated confidence intervals. Surprisingly, we are the first study within the election prediction literature to acknowledge this problem, although it is an obvious source of error [29]. Additional file 1: Figure S2 in Section S2 visualizes the variation of the 10 GT datasets. Moreover, in contrast to statements in the literature referring to data from the website [30] and the [22], we find that sometimes more than one different sample can be obtained on the same day (see Additional file 1: Table S1 in Section S2) and that drawing samples from different PCs in different networks at the same time yields the same sample when using gtrendsR. Google trends data windowsAfter having collected data from 1 January to 27 September of each election year, the question arises which data windows within these data are best suited for election prediction. As depicted in Fig. 2, data windows are defined by their width (length of time period) and distance to the election. In previous research authors rarely provided a justification for the corresponding choices. Fig. 2Logic of data windowsFull size imageIn what concerns width, the majority of studies used time window(s) with a width of 1/2 weeks or 1/3 months. In contrast, our aim is to systematically examine as many data windows as possible in order to find the best possible prediction windows and to provide guidance for future research. In doing so we compare small with large data windows. Small data windows better reflect the searches occurring in short time spans and the current mood in those time periods. Wider data windows reflect average interest across a longer time period and average out non-meaningful spikes (e. g. , TV appearances). We compare data windows of eight widths namely 7, 14, 21, 28, 42, 56, 70 and 91 days. In what concerns distance, previous studies have barely examined this aspect and have mostly chosen a distance of one day to the election. However, election campaign leaders and demoscopists will be more interested in how parties are predicted to perform at an earlier timepoint, e. g. , two weeks or three months before the election. We compare the predictive power of GT data windows of distance one to 150 days before election day. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexities and limitations in data analysis when predicting elections. It emphasizes that the study takes sampling error into account, acknowledges the variability in datasets, and stresses the need to analyze multiple data windows rather than relying on perfect predictive accuracy. The mention of sampling errors and variations highlights that prediction is not infallible, countering the idea of perfect accuracy in AI's predictions.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: Une telle manière de (ne pas) penser ce qu’est « la » technologie permet de trop faciles antithèses entre « vrais » musiciens et machines (une antithèse qui affleure beaucoup dans le chapitre sur l’EDM), ainsi qu’entre les genres musicaux « centrés sur la technologie » (le hip-hop, l’EDM) et les autres. L’auteur verse tellement peu dans l’approximation par ailleurs, qu’on est étonné de retrouver celle-ci dans son texte. Les instruments de musique – y compris acoustiques – sont bien évidemment des appareils relevant de technologies complexes. Un vrai questionnement de ce concept de technologie en musique produirait des résultats et des débats tout à fait passionnants, aussi passionnants que ceux sur le concept de liveness tels qu’Auslander en avait posé les termes en 1999. 13Enfin, on ne m’en voudra pas de remarquer que le corpus de l’ouvrage ne contient aucune femme. Il est très possible que les carrières musicales de femmes, avec tous les biais qu’on leur connaît, très bien étudiés maintenant, ne débouchent pas sur une phase posthume comme celles des hommes considérés ici. Toutefois, de la part d’un auteur qui lit et cite si généreusement des auteures et qui maîtrise avec tant d’aisance beaucoup de problématiques d’actualité en popular music studies, on pouvait espérer trouver, serait-ce au détour d’un de ses si nombreux développements centrifuges, des considérations tout à fait pertinentes sur cette regrettable disparité. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses issues related to technology in music and the representation of women in music careers. It does not address the accuracy of historical records within artifacts of any culture, thus providing no support for or contradiction against the claim.


Input: Task: corroborate the claim using the given text. Claim: Entomopathogenic nematodes can target soil-dwelling pests. [SEP] Text: , Stock, S. P. and Sternberg, P. W. ( 2012). An entomopathogenic nematode by any other name. 8: e1002527. Dolinski, C. , Choo, H. Y. and Duncan, L. W. ( 2012). Grower acceptance of entomopathogenic nematodes: Case studies in three continents. J Nematol 44: 226-235. Dutky, S. R. and Hough, W. S. ( 1955). Note on a parasitic nematode from codling moth larvae, Carpocapsae pomonella. Proceedings of the of Washington 57:244Ellers and Lynch, J. (2000). Potential of entomopathogenic nematodes for biological control of Acalymma vittatum (Coleoptera: Chrysomelidae) in cucumbers grown in conventional and organic soil management systems. J 93: 605-612. Fedorko, A. (1971). Nematodes as factors reducing the populations of Colorado potato beetle, Leptinotarsa decemlineata. Hung 6: 175-179. Finney, J. R. (1983). The feasibility of using nematodes (Heterorhabditis sp. and Neoaplectana sp. ) for control of Brassica apple and blueberry pests. Proceedings of the 13:39-41. Friedman, M. J. (1990). Commercial production and development. Pp 153–172. In: R. Gaugler, and H. K. Kaya (Eds. ) in Biological Control. Boca Raton, FL: CRC Press. Ganguly, S. and Singh, L. K. (2000). Steinernema thermophilum sp. n. (Rhabditida: Steinernematidae) from India. Int. J. Nematol. 10: 183 - 191. Georgis, R. , Poinar, G. O. Jr. , Wilson, A. P. (1983). Practical control of the cabbage root maggot, Hylemyabrassicae, (Diptera: Anthomyiidae) by entomogenous nematodes. : Infec Dis. 11:322. Georgis, R. , Wojcik, W. F. [SEP] Justify:

Output: The text corroborates the claim as it includes references to multiple studies demonstrating the effectiveness of entomopathogenic nematodes in controlling various pests such as Acalymma vittatum (the cucumber beetle) and Colorado potato beetles. The text highlights various applications and research surrounding these nematodes in reducing populations of soil-dwelling pests.


Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: , for the AfD, with the error being closer to 0 across models. For the 2021 election the error generally seems highest for the AfD. Moreover, shares of certain parties are usually underestimated (e. g. , SPD), while others are overestimated (e. g. , AfD). It seems that the quality of Google searches as a signal of vote choice differs across parties. Importantly, Figure A4 provides further visualizations for more intervals for the 2021 election, Figure A5 provide visualizations for the other elections and Table S2 also provides models for the other elections. The insights described above are largely confirmed when using data for other elections. Comparing predictions across model classesAbove, we compared different models within class MC1-GT focusing on the width and distance of data windows. Previous studies have often combined GT data with election or polling data. As described in Section ''Prediction models and benchmark'' we compare predictions across three broad classes of models. Figure 5 again focuses on the 21’ election. Fig. 5Comparing the accuracy of different modelling approachesFull size imageNow, each point represents the mean absolute error, i. e. , the prediction error averaged across parties. Figure 5 visualizes 2400 predictions (150 distances * 4 intervals * 4 models). The models are colored: MC1 models based on GT data in red, MC2 models based on GT data weighted with previous election results in purple, MC3 models based on GT data weighted with polling data in orange. Finally, we have the predictions based on polls (colored in black), whereby we simply use the last poll in the respective time windows. As in Fig. 4, the four plots in Fig. 5 (Plot 1–4) correspond to different widths of the data window. Not surprisingly, we find that polls (black line) unarguably perform the best for the 2021 election reflected in the fact that prediction error mostly scores below our GT data based models of Class MC1–3. In Fig. 5 this becomes visible as the black line is almost always closer to 0 then the other ones. We also compared how often our other models actually provide better predictions. GT data based MC1 models provide better prediction in 6% (35 out of 600) of the cases. MC2 models that weight GT data with previous election perform the worst with 0% (2 out of 600) better predictions as compared to polls by Infratest Dimap. [SEP] Justify:

Output: The text contrasts the claim by detailing that various prediction models, including those based on data trends and patterns, do not achieve perfect accuracy. It highlights that the prediction errors vary across different models and that, specifically for the 2021 election, the models based on Google Trends (GT) data perform worse than polling data, which indicates that models can lead to significant errors rather than perfect predictions.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: 14Mais ces deux remarques sont en réalité des critiques légères au regard de la somme réflexive proposée ici par Bratus. Ce livre est aussi dense que son titre et fournit aliment à la pensée pour longtemps. Il balaye un territoire très vaste. Il est plein de reliefs, le moindre n’étant pas de choisir comme clé centrale d’analyse une notion – le will to believe – issue de la pensée d’un psychologue lointain, : cela paraît un peu décalé – comme s’il reprenait un concept à Freud ou à Jung – et encore ceux-ci sont-ils plus récents que James. Après ce voyage sans guère de plan ni de boussole dans une prose analytique et théorique touffue mais souvent passionnante, on peut choisir de croire à ce que le frère de William James, Henry, appelait le « motif dans le tapis » (the figure in the carpet) : la cohérence d’une pensée au-delà du fourmillement parfois inextricable des idées. Haut de page Pour citer cet 184. Référence électronique Catherine Rudent, « Alessandro Bratus, Mediatization in Recorded Artifacts: Performance on Record and on Screen », Volume [En ligne], 18 : 2 | 2021, mis en ligne le 15 décembre 2021, consulté le 06 octobre 2024. URL : DOI : de page Rudent est musicologue, actuellement directrice du département de Médiation Culturelle de la à Paris, chercheuse au (Centre de Recherche sur les Liens Sociaux) et co-fondatrice de l’IASPM-bfE en 2005. [SEP] Justify:

Output: The text is irrelevant to the claim as it focuses on a critique of a book by Bratus and discusses theoretical concepts without addressing the accuracy of cultural history as recorded in artifacts. There are no references or arguments related to the claim within the provided text.


Input: Task: corroborate the claim using the given text. Claim: Entomopathogenic nematodes can target soil-dwelling pests. [SEP] Text: and Shetlar, D. J. ( 1989). Use of Steinernema feltiae in bait for the control of black cutworm (Agrotis ipsilon) and tawny mole crickets (Scapteriscus vicinus). 72:203-204. Ghode, M. K. , Mishra, R. P. , SwainP. K. , Nayak, U. K. and Pawar, A. D. ( 1988). Pathogenicity of Steinernema feltiae Weiser to Heliothis armigera Hubner. Bulletin (India) 40:7-8. Glaser, R. W. and Fox, H. ( 1930). A nematode parasite of the Japanese beetle (Popillia japonica Newm). Science 71: 16-17. . , LeBeck, L. M. and Mello, C. L. ( 1993). Entomopathogenic nematodes for biological control of the leaf miner, Liriomyza trifolii (Dipt. Agromyzidae) (Rhabditida: Steinernematidae). Entomaphaga 38:359-369. Hellqvist, S. , Johansson, L. and Burman, M. ( 1988). Neoaplectana carpocapsae (Nematoda) against turnip root fly (Delia floralis). Vaxtskyddsrapporter, Jordbruk 53:44Hsiao, W. F. ( 1997). Pathogenicity of entomopathogenic nematode, Steinernema carpocapsae to cabbage webworm and cabbage pyralid. Bulletin (Taipei) 39:305-312. Hunt, D. J. and Subbotin, S. A. (2016). Taxonomy and Systematics. Pp 13-58. In: David J. Hunt and Khuong B. Nguyen (Eds. ). Advances in Taxonomy and Phylogeny. and Perspectives. Vol. 12. Pub, Leiden, Netherlands. 438 pHussain, M. A. , Ahmad, R. and Ahmad, M. ( 2014). [SEP] Justify:

Output: The text corroborates the claim by providing examples of various studies and findings that highlight the pathogenicity of entomopathogenic nematodes, including Steinernema feltiae and Neoaplectana carpocapsae, to various pests such as the black cutworm, tawny mole crickets, and turnip root fly. These examples suggest that these nematodes are indeed capable of targeting soil-dwelling pests.


Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: Finally, MC3 models that combine GT data with polls perform the best with 24% (147 out of 600) of predictions being better. The picture hardly changes when we restrict our models to those based on a width of 91 days. Naturally, we could discuss whether the accuracy of our GT based models (MC1) is really so much worse than polling data given the latter’s costs. We can collect GT data for free, errors of the size found here may be acceptable for certain applications where we only need rough predictions. Besides, if we want to decrease the dependency of GT-based predictions on short-term trends we should probably base our predictions on a larger time span as shown in Plot in Fig. 5. We provide findings for other elections in Section ''Comparing predictions across model classes and elections'' and in Additional file 1: Section S4. 2. Comparing predictions across model classes and electionsAbove we focused on the most recent election in Germany (26th of September 2021). This focus is justified: Given the changing user population, the most recent election is the most appropriate to assess the predictive power of GT search data. Nonetheless, a comparison with earlier elections can provide us with some insights as to what variations we can expect for coming elections. Figure 6 is similar to Fig. 5 only that the width of the data window is held constant at 91 days which corresponds to Plot 4 in Fig. 5, and predictions for different elections are shown on top of each other (Plot 1–4). Again, each point represents the mean absolute error, i. e. , the prediction error averaged across parties whereby predictions by different model classes are colored. Fig. 6Accuracy of predictions across model classes and electionFull size imageTable 3 Comparing model predictions to pollsFull size tableWe find that indeed the accuracy of predictions varies across elections. Table 3 provides an overview regarding how often the different models where better than purely poll based predictions across elections (poll based predictions always concern the last poll). We can see that 2021 and 2009 were particular bad years for models of class MC1 and MC2 with zero better predictions than polls. In contrast, models of class MC3 provided better predictions for 20% of the estimated models both in 2009 and 2021. For the 2013 election, the purely GT data based models beat the polls in 66% of the estimated models and provide better predictions than the other model classes most of the time. [SEP] Justify:

Output: The text contrasts the claim by discussing the limitations of AI predictions, stating that the accuracy of predictions varies across elections and that errors of significant size may be tolerated for certain applications. Notably, the text mentions that in 2021 and 2009, models had zero better predictions than polls, highlighting the imperfect nature of predictive models.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: Spécialiste des musiques populaires phonographiques et des musiques de divertissement, elle questionne les représentations sociales qui structurent et mettent en tension les sons de ce champ multiforme et analyse les styles vocaux ainsi que les mélanges stylistiques résultant des équilibres culturels mondiaux. Co-directrice de l’ouvrage collectif Made in France (Routledge, 2018), autrice de L’album de chansons (Honoré Champion, 2011), éditrice scientifique du dossier La voix pop, dans Volume! en 2020. 4. 0. Les autres éléments (illustrations, fichiers annexes importés) sont « Tous droits réservés », sauf mention contraire. Haut de page Sommaire - Document précédent - Document suivant clés Géographique musical numéros 20 : 2 | 2023La fin des genres musicaux 20 : 1 | 2023La valeur de la musique 19 : 2 | 2022Terrains communs : ethnomusicologie et popular music studies 19 : 1 | 2022La scène de Canterbury Numéros en texte intégral 18 : 2 | 2021Experts - 18 : 1 | 2021Back to work 17 : 2 | 2020Le monde ou rien 16 : 2 17 : 1 | 2020La voix pop 0 : 0 | 202016 : 1 | 2019Musique & hacking 15 : 2 | 201915 : 1 | 2018 14 : 2 | 201814 : 1 | 2017 13 : 2 | 2017Stylee 13 : 1 | 2016La scène punk en France 12 : 2 | 2016studies 12 : 1 | 2015Avec ma gueule de métèque 11 : 2 | 2015 11 : 1 | 2014Souvenirs, souvenirs 10 : 2 | 2014Composer avec le monde 10 : 1 | 2013Écoutes 9 : 2 | 2012Contre-cultures n°2 9 : 1 | 2012Contre-cultures n°1 8 : 2 | 2011Sex Sells, Blackness too? [SEP] Justify:

Output: The text does not address the claim directly and seems unrelated, discussing popular music, cultural representations, and ethnomusicology. There is no mention or implication regarding the historical accuracy of cultural artifacts.


Input: Task: corroborate the claim using the given text. Claim: Entomopathogenic nematodes can target soil-dwelling pests. [SEP] Text: Evaluation of Steinernema masoodi (Rhabditida: Steinernematidae) against soil– dwelling life stages of Helicoverpa armigera (Lepidoptera: Noctuidae) in laboratory and microplot study. 2:4-8. . and Shakeela, V. ( 2000). Virulence of native entomopathogenic nematodes against black cutworms, Agrotis ipsilon (Hufnagel) and A. segetum (Noctuidae: Lepidoptera). Nematol 30:103-105Jansson, R. K. and Lecrone, S. H. (1997). Effect of sweet potato cultivar on efficacy and persistence of entomopathogenic nematodes for control of Cylas formicarius. Nematropica 27: 41-52. Jansson, R. K. and Lecrone, S. H. , Gaugler, R. and Smart, G. C. Jr. (1990). Potential of entomopathogenic nematodes as biological control agents of sweet potato weevil (Coleoptera: Curculionidae). J 83: 1818-1826. Jansson, R. K. , Lecrone, S. H. and Gaugler, R. ( 1993). Field efficacy and persistence of entomopathogenic nematodes (Rhabditida: Steinernematidae, Heterorhabditidae) for control of sweet potato weevil (Coleoptera: Apionidae). J 86:1055-1063. Josephrajkumar, A. and Sivakumar, C. V. ( 1997). Biological control potential of native entomopathogenic nematodes against Spodoptera litura (Fab. ). 5: 164-167. Kashkouli, M. , Khajehali, J. and Poorjavad, N. ( 2014). Impact of entopathogenic nematodes on Thrips tabaci Lindeman (Thysanoptera: Thripidae) life stages in the laboratory and under semi-field conditions. J Biopests 7:77-84. KayaH. K. and Gaugler, R. ( 1993). Entomopathogenic nematodes. Entomol 38: 181-206. [SEP] Justify:

Output: The text corroborates the claim by detailing various studies that evaluate the effectiveness of entomopathogenic nematodes, such as Steinernema masoodi, against soil-dwelling pests like Helicoverpa armigera and other species. The references to multiple research studies highlight the role of these nematodes in controlling pest populations, thus supporting the assertion that they can target soil-dwelling pests.


Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: For the 2017 election, the purely GT data based models fare even better, beating the polls in 97% of the models (defined by width and distance), with the other two model classes faring somewhat worse. Hence, in general, 2017 was a particularly bad year for the polls in our data. We can only speculate why there is such strong variation across elections. First, as mentioned, we have to assume that the representativity of Google search users varies across time. In principle, it is possible that the population of Google search users was more representative of German voters in the 2013, 2017 elections than in 2009 or 2021. Second, it could be related to the elections themselves. Potentially, the extend to which the action “search for” is related to “vote for” depends on the election with more “charged” elections like the 2021 election decreasing this correlation [31]. Third, it is possible that the accuracy of the polling data which we use as a benchmark varies over time. ConclusionGoogle trends data has become a popular data source for prediction in different domains such as elections. While most previous research focuses on binary electoral outcomes such as referendum results or presidential elections, we evaluate GT predictions in a multi-party setting. We developed a framework that allows us to compare predictions across 1200 fine-grained GT data windows that vary both in terms of width (7 to 91 days) and distance to the election (1 to 150 days). And, we compare predictions across several elections (four general elections in Germany). Besides, we provide a more systematic assessment hitherto neglected choices such as the selection of search terms, GT data samples and search refinement categories. Tackling these different dimensions allows us to provide some unique insights. First, we find that predictive accuracy varies significantly as a function of the width and distance of GT data windows. To some extent disagreement on the predictive accuracy of GT data in previous research may be linked to the varying choices researchers made here (cf. Table 2). In what concerns width(s), accuracy varies significantly across time for shorter data windows (here 7–28 days). We would generally recommend choosing larger data windows for predictive purposes to average out variation that is due to singular events. And, akin to classic polling data we find that predictive accuracy increases the closer our data window to the election. Second, in terms of predictive models we compared models based on GT data, on GT + previous electoral outcomes data and GT + opinion poll data. [SEP] Justify:

Output: The text contrasts the claim by discussing the limitations of predictive models based on Google Trends data, noting that predictive accuracy varies significantly based on factors such as the width and distance of the data windows and the nature of the elections. It highlights that while Google Trends data has become popular for predictions, the accuracy is not perfect and is influenced by numerous variables.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: 8 : 1 | 2011Peut-on parler de musique noire 7 : 2 | 2010BIS 7 : 1 | 2010dans les musiques populaires 6 : 1-2 | 2008Géographie, musique et postcolonialisme 5 : 2 | 2006Les Scènes metal 5 : 1 | 2006musicale alternative 4 : 2 | 2005Musiques actuelles : un “pas de côté” 4 : 1 | 2005Musiciens-sociologues 3 : 2 | 2004Sonorités Hip-Hop 3 : 1 | 2004à l'épreuve du populaire Musiques électroniques 3 : 0 | 2004Rock et Cinéma 2 : 2 | 2003Music 2 : 1 | 2003 1 : 2 | 2002 1 : 1 | 2002 Tous les numéros La revue Volume Les Éditions Mélanie Seteun & Volume La Rédaction & les Comités de lecture Volume! in English! Instructions aux auteurs, processus éditorial et diffusion Acheter s'abonner Informations : citation, reproduction, diffusion Nos liens S’inscrire à la newsletter de Volume Actualités Contacts & Crédits Politiques de publication La collection "Musique & Société" La collection sur OpenFaire carrière dans le rap au « Plus que la musique… » des musiques populaires au xxie siècle le rap sort de sa bulle et ses publics Stéréo du rock de la culture Hard rock, heavy metal, metal Les mots distordus techno La collection "Musique & Environnement Professionnel" Présentation La Création dans les musiques traditionnelles en pratiques collectives en amateur dans les musiques populaires L’emploi permanent dans les lieux de musiques actuelles La coopération entre projets de musiques actuelles La diffusion dans les lieux de musiques actuelles Actions culturelles et musiques actuelles Vibrations Vibrations. [SEP] Justify:

Output: The text is irrelevant to the claim as it does not address the accuracy of cultural history recorded in artifacts. Instead, it consists of a list of publications and topics related to music, which do not pertain to the recording of cultural history or artifacts.


Input: Task: corroborate the claim using the given text. Claim: Entomopathogenic nematodes can target soil-dwelling pests. [SEP] Text: Kaya, H. K. and Grieve, B. J. ( 1982). The nematode Neoaplectana carpocapsae and the beet armyworm Spodoptera exigua: Infectivity of prepupae and pupae in soil and of adults during emergence from soil. J 39: 192-197. Kondo, E. ( 1987). Size-related susceptibility of Spodoptera litura (Lepidopter: Noctuidae) larvae to entomogenous nematode, Steinernema feltiae (DD-136). Zool 22:560-569. LaznikZ. , Toth, T. , Lakatos, T. , Vidrih, M. and Trdan, S. ( 2010). Control of the Colorado potato beetle (Leptinotarsa decemlineata) on potato under field conditions: a comparison of the efficacy of foliar application of two strains of Steinernema feltiae (Filipjev) and spraying with thiametoxam. J Prot 117:129-135. LeBeck, L. M. , Gaugler, R. , Kaya, H. K. , Hara, A. H. and Johnson, M. W. ( 1993). Host stage suitability of the leaf miner Liriomyza trifolii (Diptera: Agromyzidae) to the entomopathogenic nematode Steinernema carpocapsae (Rhabditida: Steinernematidae). J 62:58-63. Lossbroek, T. G. and Theunissen, J. ( 1985). The entomogenous nematode Neoaplectana bibionis as a biological control agent of Agrotis segetum in lettuce. Nematol 39: 261-264. Mannion, C. M. and Jansson, R. K. ( 1992). Movement and post infection emergence of entomopathogenic nematodes from sweet potato weevil, Cylas formicarius (F. ) (Coleoptera: Apionidae). 2:297-305. Mannion, C. M. and Jansson, R. K. ( 1993). Within root mortality of Cylas formicarius (Coleoptera: Apionidae) by entompathogenic nematodes. [SEP] Justify:

Output: The text supports the claim by providing references to various studies involving entomopathogenic nematodes, such as Neoaplectana carpocapsae and Steinernema feltiae, targeting specific soil-dwelling pests like the beet armyworm (Spodoptera exigua) and the Colorado potato beetle (Leptinotarsa decemlineata). These examples demonstrate the efficacy of these nematodes as biological control agents against soil-dwelling pest species.


Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: Generally, high quality opinion polls, in our case by the renowned company Infratest Dimap, still represents the benchmark in terms of accuracy, especially in the case of the latest election in 2021. We found that models that combine polling data with GT data (MC3) data fare better than purely GT-data-based models (MC1). Furthermore, we find that weighting GT data with previous electoral outcomes [14] does not help predictive accuracy, at least not for the German case (cf. Fig. 5). Third, while we argued that recent elections are the appropriate benchmarks for GT data predictions, comparisons to past elections may still be revealing. Especially, insofar our findings for the 2021 election are somewhat discouraging, which goes against earlier studies that emphasize the predictive accuracy of GT data. Hence, we need to test whether our findings for 2021 also hold for other elections. And, especially for the 2013 and 2017 election GT data models where much more accurate, at times beating or at least aligning with predictions based on opinion polls (cf. Fig. 6). Above we speculated that the nature of the election may affect the predictive power of GT data (cf. [31]). More generally, this highlights that conclusions regarding predictive accuracy from one election may not generalize to other elections. Finally, we conclude that GT prediction research should ideally become more transparent. From our review we learned that identifying the various characteristics in Table 1, i. e. , all representing important choices when using GT data, was a challenge. Future research would benefit if authors would report more details, e. g. , the exact time of GT data collection, the number of GT samples, the nature of search term selection. For instance, we found that it matters which category search filter is selected (see Additional file 1: Section S1). Our study has several limitations that provide venues for future research (see [32] for a systematic discussion of limitations and a literature review). First, we pursued a systematic approach to search term selection, testing different search terms against each other (see Section ''Search terms and category filter''). Future research might benefit from choosing an even wider net of search terms, trying out different ones. Second, while we predicted elections shares we did not forecast them in that the elections happened already. Since, we didn’t built any sophisticated models we somewhat circumvented the danger of adapting our models to already seen data. [SEP] Justify:

Output: The text contrasts the claim by illustrating that models based on GT data do not always result in accurate predictions, particularly for the 2021 election. It indicates that while some models may perform well, the predictive accuracy is inconsistent and cannot be generalized across different elections. Specifically, it suggests that conclusions about predictive accuracy drawn from one election may not apply to others, indicating limitations in AI’s ability to predict the future with perfect accuracy.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a 10. 21203/rs. 3. rs-3508816/v1This work is licensed under a CC BY 4. 0 LicenseStatus:Published10 May, 2024Read the published version in →Version 1posted 7You are reading this latest preprint versionAbstractpurpose of this study is to analyze an automated voice to text translation device by reportingt he translation accuracy for recorded pediatric neurosurgery clinic conversations, classifying errors in translation according to their impact on overall understanding, and comparing the incidence of these errors in English to Spanish vs. Spanish to English conversations. and Spanish speaking patients at a single academic health system’s outpatient pediatric neurosurgery clinic had their conversations recorded. These recordings were played back to a handheld smartphone with voice to text translation software. A certified medical interpreter evaluated recordings for incidence of minor errors, errors impacting understanding, and catastrophic errors affecting patient-provider relationship or care. Two proportion t-testing was used to compare these outcomes. Results 50 patient visits were recorded: 40 English recordings translated to Spanish and 10 Spanish recordings translated to English. The mean transcript length was 4244 ± 992 words. The overall accuracy was 98. 2% ± 0. 5%. On average, 46 words were missed in translation (1. 09% error rate), 31 understanding-altering translation errors (0. 73% error rate), and 0 catastrophic errors were made. There was no significant difference in English to Spanish or vice versa. to text translation devices accurately translate recorded clinic conversations between Spanish and English and vice versa with high accuracy and very low incidence of errors impacting medical care or understanding. Further study should investigate additional languages as well as compare these devices directly to medical interpreters in live clinic settings. to CareQuality ImprovementIntroductionPatient-provider communication is vital to patient care and safety, and previous studies have linked effective communication with reduced malpractice claims and improved outcomes. 1,2 However, effective patient-provider communication is not always easily achieved. Thorough but simplified explanations of procedures, preparation, and post-operative care and expectations are expected from clinicians even in brief clinic visits, which can be complicated by language and cultural barriers. [SEP] Justify:

Output: The text does not provide any information related to the claim about cultural history being recorded in artifacts. Instead, it discusses a study on voice-to-text translation accuracy in medical settings, which is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Entomopathogenic nematodes can target soil-dwelling pests. [SEP] Text: J 86:722-729. Masaaod, Z. , Ayatallah, S. , Habib, A. , Ali, J. and Ali, A. Y. (2015). Efficacy of entomopathogenic nematode Steinernema carpocapsae against the diamondback moth, Plutella xylostella (L. ) in laboratory condition. 48: 393-399. Mason, J. M. and Wright, D. J. ( 1997). Potential for the control of Plutella xylostella larvae with entomopathogenic nematodes. J Inverte Pathol70: 234-242. Mathasoliva, J. B. , Maghodia, A. B. and Vyas, R. V. ( 2004). Efficacy of Steinernema riobrave against Agrotis ipsilon Hufnagel (Lepidoptera: Noctuidae) on Potato. Nematol34: 117-179. and Malik, V. S. (2002). Evaluation of entomopathogenic nematodes for suppression of carrot weevil. Biocontrol 47: 545-561. Narayanan, K. and Gopalakrishnan, C. (1987). Effect of entomopathogenic nematode Steinernema feltiae (Rhabditida: Steinernematidae) to the pre-pupa, pupa and adult of Spodptera litura (Noctuidae: Lepidoptera). Nematol 7:273-276. Nastaran, R. , Javed, K. , Mojtab, H. , Morteza, G. and Raquel, C. H. ( 2015). Pathogenicity of two species of Entomopathogenic nematodes against the greenhouse whitefly Trialeurodes vaporariorum (Hemiptera:Alevrodidae), in laboratory and greenhouse experiments. J Nematol 47:60-66. Nyasani, J. , Kimenju, F. , Olubavo, S. , Shibairo, A. and Mutua, G. ( 2008). Ocurrence of entomopathogenic nematodes and their potential in the management of diamondback moth in Kale. [SEP] Justify:

Output: The text corroborates the claim by providing examples of various studies that highlight the efficacy of different species of entomopathogenic nematodes against specific pests, including the diamondback moth and the carrot weevil. These studies suggest that entomopathogenic nematodes have been evaluated for their effectiveness in controlling soil-dwelling pests, thereby supporting the idea that they can target such organisms.


Input: Task: contrast the claim using the given text. Claim: AI can predict the future with perfect accuracy by analyzing data trends and patterns. [SEP] Text: Nonetheless, as is now more common in the literature on election forecasting [33], studies that rely on GT data for prediction could also be pre-registered. Third, from the general perspective of election forecasting, GT data could be seen as just another dynamic signal that can be integrated into more sophisticated modelling strategies (e. g. , [4, 34]) that go beyond the weighting approach used in the present paper. Whether such additional sources of data can improve predictions remains to be tested. Fourth, the changing predictive power of GT across elections may be related to (1) how representative the GT data is of searches on the platform and (2) how representative users of the GT platform are of voting the population. Pertaining to (1), both aspects of representiveness should be studied further. Finding variation across GT data samples Raubenheimer et al. [21] suggested that there might be a publication bias, i. e. , successful predictions are based on suitable samples. For this reason we averaged across GT data samples (cf. Section ''Collecting GT data'' and Additional file 1: Section S2). However, more research into the variability of such samples for particular predictions is warranted. And, user representativity (2) is relevant as well. Platforms are generally quite secretive about their userbase. Collecting more evidence on how representative Google users are of the general (voting) population would help to explain the accuracy of corresponding predictions and help to develop more sophisticated weighting schemes. Availability of data and materials Code and data to reproduce the study are available in the Additional file 1: NotesMore recently, scholars have turned to using reweighted non-representative polls to predict elections (e. g. , [5]). Available Operators: No quotation marks (results for each word in your query), Quotation marks (coherent search phrase), Plus sign (serves as function of an OR-operator) and Minus sign (Excludes word after the operator) (Help 2023d). Possible to compare up to five groups of terms at one time and up to 25 terms in each group (Help 2023a). [SEP] Justify:

Output: The text contrasts the claim by highlighting the limitations and uncertainties in using GT (Google Trends) data for predictions. It discusses the need for further research to determine the predictive power and representativeness of the data, emphasizing that whether additional data sources improve predictions remains untested. This implies that AI cannot achieve perfect accuracy in predictions.


Input: Task: pass the claim using the given text. Claim: Every culture's history is accurately recorded in their artifacts. [SEP] Text: 3 Further, physicians must adapt their mode of communication depending on knowledge and level of healthcare literacy possessed by the individual patient and their family,4 especially in medical subspecialties, such as neurosurgery, that involve complex and often uncertain diagnoses and prognoses. 1 Neurosurgery involves the treatment of high-acuity patients whose cases are often complicated and highly unique, with even the most common surgeries imposing serious morbidity risks. 5 This warrants additional attention be paid to careful and thoughtful communication throughout the entirety of a patient’s treatment. Pediatric settings can be especially emotional and sensitive,6imposing circumstances in addition to the already challenging task of adequately communicating neurosurgical terminology and treatment options. When a language barrier is present between pediatric patients, their caregivers, and their physician, an additional layer is encountered by pediatric physicians as they navigate patient communication. 7 As the (US) population continues to diversify, the challenges posed by language barriers has increased strain on healthcare systems. Americans projected to comprise nearly 25% of the US population by 2050, prior studies have found that only 6% of physicians identify as bilingual, necessitating the use of translation modalities for physicians who lack the ability to effectively communicate in the patient’s primary language. 8 In-person medical interpreters, the standard of care, are trained in medical terminology and maximize effective patient communication. 9 While in-person interpreters remain the standard in the clinical setting, the number and availability of in-person interpreters has been far outpaced by the demand for interpretation, leading to the rise of telemedicine and facilitating the development of multiple translation devices, as well as remote “phone interpreters. ”9 These adjunct translation services, while important for the accessibility of translated medical care, have not been characterized in the current literature. More specifically, there is little available data regarding the reliability of translation devices in neurosurgical clinic settings. Thus, this study set out to assess the accuracy of the voice to text translation device as a potential method for augmenting patient-provider communication in Spanish-speaking populations in the pediatric neurosurgery clinic setting. The purpose of this study is thus to evaluate the accuracy of a voice to text handheld medical translation device in translating recordings, characterize the impact of inaccuracies on overall conversation understanding, and compare these metrics for English to Spanish and Spanish to English conversations. [SEP] Justify:

Output: The text discusses the challenges of communication in medical settings, particularly concerning language barriers and translation services in pediatric neurosurgery. It does not address the accuracy of historical records in cultural artifacts, making it irrelevant to the claim.