Input: Task: contrast the claim using the given text. Claim: AI will fully replace human teachers in the next decade. [SEP] Text: 5 found that, like humans, it tends to overestimate how widespread its opinions are in the general population, a bias known as the false consensus effect. But unlike humans, the model showed little hesitation in taking risks and tempting fate. Marcel Binz, a cognitive scientist at the Institute for Biological Cybernetics, says AI might need to physically interact with the world to exactly mimic human participants; it’s hard to learn all the nuances of intelligent behavior just through passive reading. But he thinks AI will progress quickly in any case. “It is plausible that we will have a system within a few years that can just be placed into any experiment and will produce behavior indistinguishable from human behavior. ” A critical question is whether language models will not just reproduce existing findings, but generalize and predict new ones. When models appear to match published psychology studies, they could be regurgitating training data in response to memorized questions. As a result, many researchers are taking pains to phrase questions in novel ways. Another lingering issue is whether models reflect what people would actually do or just what they say they’d do. People often lie to researchers—and even themselves. co-founder suspects the models state true p3. She and her colleagues found that, like the people in the original experiment, the model didn’t begin to let off the button until 300 volts. Aher thinks the models could provide guidance in other sensitive arenas that are difficult to study, for example, what to say to a person who is suicidal. Gray says researchers could study ostracism, or the role of negative feedback on self-esteem. Or, he says, they could study dehumanization of the kind seen in the Vietnam War’s My˜ Lai massacre by describing the situation and asking a model what it would do—provided the models aren’t too sanitized. Argyle says she doesn’t know of anyone yet who has replaced human participants with language models. “To be honest, this is all still pretty much a hypothetical,” she says. “First we have to demonstrate the language models can do the work. ” believes the shift is inevitable. It reminds him of a similar transformation a decade ago, when many social science experiments moved from in-person to online surveys. “People were like, ‘How can you run experiments online? Who are these people? [SEP] Justify:

Output: The text contrasts the claim by indicating that it is still hypothetical whether AI can fully replace human participants in many contexts, including teaching. Marcel Binz notes that while AI might progress rapidly, there is still no evidence that language models can adequately perform tasks that require the nuances of human behavior. Furthermore, Argyle highlights the absence of instances where human participants have been fully replaced by AI models, suggesting that significant challenges remain before AI can assume the role of teachers.


Input: Task: pass the claim using the given text. Claim: The study of folklore can provide insights into cultural perceptions of nature. [SEP] Text: The DSM does not explain what impairment or distress might mean in relation to tobacco use, and researchers have always assumed that anyone who satisfies the diagnostic criteria has “clinically significant impairment or distress” [48]. Table 3 lists the diagnostic criteria for Disorder under DSM-5 along with some criterion-specific observations. Only two criteria must be met to satisfy the DSM-5 requirements for a psychiatric diagnosis of tobacco use disorder. Tobacco users satisfy the DSM-5 tobacco use disorder criteria when they reach the craving stage of physical dependence. The presence of craving would satisfy criterion 4 “Craving, or a strong desire or urge to use tobacco” and smoking to alleviate that craving would satisfy criterion 11b “Tobacco (or a closely related substance, such as nicotine) is taken to relieve or avoid withdrawal symptoms. ” Since all individuals at the craving stage of physical dependence smoke to relieve their craving, simply establishing that an individual has reached the craving stage of physical dependence is equivalent to a DSM-5 diagnosis of tobacco use disorder. Although the medical and psychiatric approaches to diagnosis come from different perspectives, in practical terms, using the instrument in Table 2, tobacco dependence as a medical disorder can be diagnosed at the wanting stage of physical dependence, while DSM-5 tobacco use disorder can be diagnosed at the craving stage. The implication here is that researchers should recognize that dependence as a medical disorder may be present in individuals who do not meet DSM criteria for a psychiatric disorder; researchers should not limit their focus to individuals who meet DSM criteria. Dependence onset in relation to smoking frequencyCraving after having smoked only a few cigarettes is common. [17, 28, 49, 50] In a survey of 34,000 adolescents who had tried smoking, craving or other dependence symptoms were reported by one third of those that had smoked 3 or 4 tobacco cigarettes, and by half of those that had smoked 10–19 cigarettes [28]. By the reasoning described above, half of adolescent smokers meet DSM-5 diagnostic criteria for tobacco use disorder before they have smoked a whole pack of cigarettes. This should not be surprising given the rapidity with which nicotine triggers enduring neuroplastic changes in the brains of experimental animals (see [26] for a review). Neuroplastic changes have been observed after a single dose of nicotine in animal studies [51]. Each of the first 100 cigarettes appears to promote shortening of the latencies and the appearance of additional symptoms. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses diagnostic criteria and aspects of tobacco use disorder, with no mention of folklore or cultural perceptions of nature.


Input: Task: corroborate the claim using the given text. Claim: Horizontal gene transfer allows bacteria to acquire new traits. [SEP] Text: Salinibacter was isolated from a salt cistern, which is the saltiest habitat known to harbor bacteria (Mongodin et al. , 2005). None of the other extremely halophilic bacteria in this dataset reach the ultra-extreme halophily of Salinobacter (Hirschler-Rea, 2003; Hou et al. , 2004; Mongodin et al. , 2005; Auman et al. , 2006; Hoeft et al. , 2007). is an exception among the six halophilic bacteria examined here in its extensive sharing and transferring of genes with archaea, and this may be related to its extreme halophily. We do not deny that halophilic archaea have been changed by horizontal gene transfer with bacteria. However, the ancient transfer of 1,000 bacterial genes that allowed the class Haloarchaea to form from methanogens (Nelson-Sathi et al. , 2012) would not be marked as transferred in our scheme because the genes are present in several genera. Additionally these genes don’t appear to be shared specifically with other modern sequenced halophilic bacteria. Correlation with genome %GC Along with oxygen utilization and growth temperature range, bacterial genome %GC content was also a significant factor correlated with the number of shared genes (Table 1). As has been noted previously (Naya et al. , 2002; Wu et al. , 2012), in our dataset aerobic bacterial genomes have a significantly higher %GC (59%) than anaerobic bacterial genomes (45%; p < 0. 001) but GC content does not correlate with oxygen utilization in archaea. Similar to Hurst & Merchant (2001), GC content does not correlate between temperature groups in either archaea or bacteria in our dataset. To verify that %GC is not confounding the effect described above for anaerobes and (hyper)thermophiles, we repeated our analyses after correcting for both genome size and genome %GC by multiple linear regression (Fig. S4). The magnitude of the %GC correction (average of 2. 6 per 10% GC change) was much smaller than that for the original genome size correction (average 45 per 1,000 genes). Interestingly, a relationship between GC content and reciprocal blast hits was only significant for aerobic archaea (p < 0. 01). [SEP] Justify:

Output: The text corroborates the claim by discussing the extensive sharing and transferring of genes between Salinibacter and archaea, which aligns with the concept of horizontal gene transfer enabling bacteria to acquire new traits. It specifically mentions that halophilic archaea have been changed by horizontal gene transfer with bacteria, supporting the idea that this process contributes to genetic variation and adaptation in bacterial species.


Input: Task: contrast the claim using the given text. Claim: AI will fully replace human teachers in the next decade. [SEP] Text: AI replace doctors’ ‘gut instincts’? Published on December 20, 2023 Doctors’ intuition plays a key role in healthcare, even when computers suggest another treatment approach. But with AI advancing, is that all about to change? Use + rapid advances in the field, AI won’t supplant human healthcare workers in 2024. : Pexels: to use -Edquist DOI 10. 54377/02d2-eea4 Doctors’ intuition plays a key role in healthcare, even when computers suggest another treatment approach. But with AI advancing, is that all about to change? The value of healthcare workers’ intuition in effective clinical care has been verified by reports around the world again and again. From doctors’ ability to spot sepsis in critically ill children, to ‘nurse worry‘ as a ‘vital sign’ predictive of patient deterioration, to helping GPs navigate complex patient care — intuition appears to play a large role in supporting high risk patients — even when data or computer outputs suggest another treatment approach. (AI) has already begun to transform healthcare, and the health sector will only continue to consider AI innovations in 2024 and beyond. In this increasingly technological world, questions swirl on what is the role of these human hunches in healthcare practice and whether AI is about to overtake doctors’ ‘gut feelings’ entirely. What is AI in healthcare and when is it used? Davenport from and Deloitte consultant explain elsewhere, AI healthcare includes ‘rule-based expert systems’, which use prescribed knowledge-based rules to solve a problem, and ‘robotic process automation’, which uses automation technologies to mimic some tasks of human workers. Such technology can help with automated patient monitoring, where alerts are signalled once a rule criterion is met, patient scheduling reminders and medicine management. Other forms of AI used in healthcare include robots, natural language processing and machine learning. Robots can help move and stock medical supplies, lift and reposition patients and assist surgeons. hospital has launched a €7 billion project, set to be completed in 2028, which will engage robots to collect patient data typically reliant on human physical touch: from measuring pulse, to taking temperature and calculating oxygen saturation. The release of ChatGPT in 2023 marked a leap forward for AI in popular consciousness. [SEP] Justify:

Output: The text contrasts the claim by discussing the ongoing role of human intuition in healthcare, emphasizing that while AI is advancing and transforming the field, it does not fully replace human healthcare workers. This serves as an analogy to suggest that similarly, while AI may be incorporated into education, it is unlikely to fully replace human teachers, thereby challenging the claim.


Input: Task: pass the claim using the given text. Claim: The study of folklore can provide insights into cultural perceptions of nature. [SEP] Text: [17, 28, 37, 49] The prevalence of craving and other symptoms increases to about 95 % among youth who have smoked 100 or more cigarettes [17, 52, 53]. In relation to smoking frequency, symptoms of physical dependence are reported by 82 % of youth who smoke at least once per week but not every day, and by 95 % of daily smokers [52]. Consistent with reports of latencies of four weeks or more, 46 % of youth who were smoking less than once per month experienced symptoms of physical dependence [17, 29, 49, 54]. Similarly, in a national survey nearly half of youths who smoked as few as 1–3 days per month reported having experienced at least one symptom of nicotine dependence [43]. Growth in the number of symptoms of dependence reported is greatest at the lowest levels of exposure in terms of days smoking per month or cigarettes smoked per day [43]. Symptom development tends to plateau when daily consumption reaches 6–15 cigarettes [43]. PrognosisThe prognosis for adolescent tobacco dependence is poor. Early symptoms of dependence predict continued and escalating smoking [37]. Shortening latencies promote an escalation in smoking frequency, while more frequent smoking promotes the progression of dependence in a mutually reinforcing cycle [45, 53, 55]. The number and intensity of the symptoms experienced by very light smokers is disproportionate to their tobacco consumption, with some nondaily smokers describing their withdrawal symptoms as unbearable [56–58]. Many nondaily smokers have failed at one or more attempts to quit, and, in cessation studies, nondaily and daily smokers relapse at the same high rates [54, 59–62]. The first insights into how tobacco dependence develops came from observing that youths who used tobacco infrequently reported significant difficulty in stopping their use. It might be a fruitful first approach to ask infrequent users of other substances if they have ever failed in an attempt to stop using the drug. Because relapse rates are very high even before the onset of daily use, craving is a grave prognostic indicator even at minimal levels of tobacco use [59, 60]. Youth become aware of craving, on average, when they are smoking two cigarettes per week [59, 60]. In a 12-year longitudinal study, smoking two cigarettes per week at age 12 increased the risk of progressing to heavy adult smoking with an odds ratio of 174 [38, 63]. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses tobacco dependence and youth smoking behavior without any mention of folklore or cultural perceptions of nature.


Input: Task: corroborate the claim using the given text. Claim: Horizontal gene transfer allows bacteria to acquire new traits. [SEP] Text: A two-way of the secondary residuals indicated that oxygen utilization and growth temperature of the bacteria were still significant factors affecting numbers of RBHs (aerobic vs. anaerobic R = 0. 382 p = 0. 001; mesophilic vs. hyperthermophilic R = 0. 676p = 0. 001). address the question of whether bacteria and archaea from the same habitats are more likely to engage in HGT, we categorized the DarkHorse and RBH results by the environment from which the archaea and bacteria were isolated. Habitats with similar temperature and oxygen characteristics, such as terrestrial hot springs and marine hydrothermal vents, have similar numbers of horizontally transferred genes and RBHs between bacteria and archaea (Fig. 8). A similar correspondence was observed with animal guts and sediments, both of which harbor a high proportion of anaerobic organisms involved in the degradation of complex organic matter (Fig. S7). These findings suggest that metabolic and physiological similarities could be more important in determining successful gene transfers between archaea and bacteria than co-habitation. However, our database does not include bacteria and archaea isolated from exactly the same area, which would be needed to examine this question more thoroughly. Figure 8: Comparison of transferred and shared genes with habitat. Comparison of transferred (A) and shared (B) genes with habitat. Particularly, we compare genes in hotsprings and hydrothermal vent bacteria to hotsprings and hydrothermal vent archaea. HGT stands for horizontally transferred genes, and RBH stands for reciprocal best hits or shared genes. Download full-size image DOI: 10. 7717/peerj. 3865/fig-8 Our findings do suggest that HGT is more common in some habitats than others. Oil wells, hot springs, and sediments are environments where bacteria and archaea share unusually large numbers of genes (Fig. 5B). 30% of bacteria with HGT genes >2 standard deviations above the mean were from hot springs, 32% were from sediments and 20% were from soil (Fig. 7). Thermophiles employ various mechanisms to mitigate DNA degradation at high temperatures, so thermophile-derived DNA may be more likely to persist both inside and outside of cells. [SEP] Justify:

Output: The text corroborates the claim by discussing horizontal gene transfer (HGT) and how it occurs between bacteria and archaea in various habitats. It mentions that HGT is more common in specific environments and identifies examples, such as hot springs and sediments, where bacteria and archaea share large numbers of genes. This supports the idea that HGT enables bacteria to acquire new traits.


Input: Task: contrast the claim using the given text. Claim: AI will fully replace human teachers in the next decade. [SEP] Text: This type of AI, which requires training on large data sets (supported by human feedback), focuses on giving computers the ability to read, support and manipulate human language. Such natural language processing has changed the communication landscape with its language mimicry. While some note that the hype hasn’t quite been reflected in reality, professionals in a range of sectors — including healthcare — now use ChatGPT for correspondence, such as with drafting “sick notes”, medication management, or to manage healthcare information. There are predictions that healthcare Processing will be a $USD7. 2 billion business by 2028, with this type of AI being deployed to help translate complex published papers for public consumption, for analysis of electronic health records to help identify at-risk patients, and to interact with patients to help with triage or answer healthcare questions. In 2024, some say this type of AI is likely to focus on more sophisticated language models that power chatbots and virtual assistants, and will be built into word processing programs. gives computers the ability to learn without explicitly being programmed for a given task. The algorithms driving these types of AI are based on statistical and predictive models. often relies on ‘training’ from existing data sets, which have been human reviewed and annotated. Essentially, doesn’t automatically know what to look for, and without human-informed training this type of AI tends to provide lots of noise and useless predictions. Once trained, can take previously unseen patient information and apply its prior ‘training’ to analyse the data and predict outcomes, or make recommendations. In healthcare, can recognise patterns which may be missed by humans such as described for AI’s role in patient survival of gastric cancer, identification of primary causes of cancers, and reducing breast cancer false positives. In 2024, algorithms are likely to continue to be used for probing healthcare data analytics, with vast medical data provided by wearables, medical devices and electronic health records. With all forms of healthcare AI — it is clear that humans are still needed for AI training, evaluation of outputs, and considering the impacts of the AI recommendation. Artificial versus human intelligence: Who has the edge? Given the global healthcare workforce shortages, the proverb may be true: Necessity breeds invention. [SEP] Justify:

Output: The text contrasts the claim by emphasizing that while AI technologies can assist in various fields, including healthcare, there is a clear indication that human involvement remains crucial. It states that professionals are still needed for 'AI training, evaluation of outputs, and considering the impacts of the AI recommendation,' which undermines the idea that AI could fully replace human teachers, as it highlights that human intelligence and oversight are still necessary in AI implementations.


Input: Task: pass the claim using the given text. Claim: Natural environments can reduce stress and improve mental health. [SEP] Text: 1 BackgroundMental health crisis is defined as “occurring when the level of distress and risk presented by a young person is not adequately supported or contained by the system that is in place for them. ” [1] (p. 13). Although over half of mental health disorders arise during adolescence, and the greatest benefits of mental health interventions are attained when implemented as soon as possible after onset of symptoms [2], it is estimated that only 25% of children and young people with a diagnosable mental health disorder are receiving treatment in the UK [3]. With the lack of early support being accessed by young people experiencing adverse mental health, it is unsurprising that the number reaching crisis point is growing. Unfortunately, in the UK, Child and (CAMHS) are not always able to meet the demand for their services, leading to long wait times for specialist mental health support, and ultimately leading to more young people reaching crisis point [4]. Possible ramifications of not addressing poor mental health in childhood and adolescence are the likelihood of mental disorders continuing into adulthood, impacting both mental and physical well-being, which could potentially limit opportunities to live a fulfilled life [5]. However, not only can poor mental health and mental health crisis have long-term consequences, but also severely damaging short-term effects, including suicidal ideation, self-harm, and currently one of the leading causes of death for children and young people in the UK, suicide [6]. In 2015, the Commission’s report, Right here, right now [7], reviewed the quality and effectiveness of crisis services in the UK and found them to be insufficient, often leading those in crisis to attend A&E as they had nowhere else to go. Furthermore, when attending A&E in crisis, less than half of young people reported a positive experience [7], along with other crisis services, A&E was scrutinised for being “under-resourced, understaffed, and overstretched” [8]. As a result, crisis services have been at the forefront of the mental health service reform agenda in the England, with the call to improve crisis services evident in key health documents, including the Concordat [9], Future in Mind [3], and the for [10]. The development of crisis mental health services continues to be at the forefront of policy in the UK and internationally [11]. [SEP] Justify:

Output: The text does not provide any information about the effect of natural environments on stress or mental health. Instead, it discusses the lack of mental health support available for young people in the UK and the consequences of poor mental health. Therefore, it is irrelevant to the claim being analyzed.


Input: Task: corroborate the claim using the given text. Claim: Horizontal gene transfer allows bacteria to acquire new traits. [SEP] Text: This biochemical characteristic of thermophiles has been previously suggested as a possible cause for the greater prevalence of HGT events between thermophiles compared to halophiles (Rhodes et al. , 2011). Furthermore, oil wells and hot springs are typically dominated by biofilm communities (Blenkinsopp & Costerton, 1991; Meyer-Dombard et al. , 2011; Marks et al. , 2012), which are known to facilitate HGT due to the high density and close physical proximity of metabolically active cells (Molin & Tolker-Nielsen, 2003; Aminov, 2011). Sediments and soil also have a high density of microbial cells (Christensen, Hansen & Sørensen, 1999; Schippers et al. , 2012). Additionally, viral abundance and production in sediments is high compared to the water column (Danovaro et al. , 2008), and more than half of the DNA in sediments is extracellular (Dell’Anno & Danovaro, 2005). Therefore, all of these factors (cell density, viral abundance, and extracellular DNA) may promote HGT in sediments. Functional characterization of shared and transferred genes To gain more insight into the types of genes that may be shared more frequently between anaerobic and (hyper)thermophilic organisms, we examined the shared genes (RBHs) by functional category using the COG database (Tatusov et al. , 2003) (Table S5). Some COG categories are more likely than others to contain genes shared between bacteria and archaea. Specifically, the categories Energy Production, Translation, Nucleotide Metabolism, and contain a higher proportion of archaea-bacteria RBHs than that found in the total set of genes in all genomes (Fig. 9). Curiously, HGTs identified by DarkHorse are not enriched in these same categories; instead, they are more abundant in Transport and Metabolism (such as metal or sodium transporters), and Conversion, and Transport and Metabolism (Fig. 9B). [SEP] Justify:

Output: The text corroborates the claim by discussing horizontal gene transfer (HGT) in the context of thermophiles and biofilm communities. It explains that factors like high cell density and the presence of extracellular DNA in sediments create conditions that facilitate HGT, which supports the idea that bacteria can acquire new traits through this process. The mention of functional characterization of shared genes further illustrates how HGT contributes to the genetic diversity among bacteria and archaea.


Input: Task: contrast the claim using the given text. Claim: AI will fully replace human teachers in the next decade. [SEP] Text: It may not be long until healthcare includes integrated AI forms where a robot greets you in your native language for your annual check-up using Processing, takes your vital signs, and sends a recommendation to the doctor on which patient to prioritise and what investigations need to be ordered using algorithms designed to analyse collected vital signs. What AI can’t do is replace the natural ‘gut feel’ of a healthcare professional. And this won’t change in 2024. The clinical reasoning and thinking process that healthcare providers engage is so complex, and the sources of information that the human brain considers in patient care are too numerous to capture with current algorithms. The implicit knowledge an expert relies on for effective clinical care is so deeply embedded in human automation, that methods to get at these data points often fail. On top of this, AI-accessible data and the AI algorithms themselves can have flaws. Machine learning can be overly sensitive, leading to over-diagnoses in some patients. Processing AIs can act as healthcare trojan horses, where the technology is so convincing in its communication approaches that it tricks the user into thinking it is knowledgeable in the same way a human is. There are also privacy concerns with such AI applications. AI typically relies on data input to continue learning — and the clarity about what happens to confidential patient information when input into AI remains an open question for many platforms. There are also challenges that the healthcare AI field is tackling related to bias and responsibility, and questions about what we consider ‘mundane’ and ‘repetitive’ tasks which AI can truly take off humans. In reality (ironically), all existing AI is devoid of the necessary context within which healthcare occurs. It misses the complexity, the empathy, and important data points that human intelligence has access to, and can therefore only replicate specific human tasks. Our healthcare future: Humans leading, AI supporting A better description of the role of AI in healthcare in the future might be: “AI won’t replace the doctors, but those doctors will be replaced who don’t use Artificial Intelligence,” as Reddy, director at India’s Apollo, has put it. Healthcare AI is increasingly taking on roles of “clinical decision-making support”, meaning the healthcare provider is in charge and human intelligence is prioritised, while AI augments this. [SEP] Justify:

Output: The text contrasts the claim by emphasizing that AI cannot replicate the nuanced reasoning, empathy, and contextual understanding that human professionals, such as healthcare providers, possess. It states that while AI can assist and augment human roles, it lacks the ability to fully replace them due to the complexity of human thought processes and implicit knowledge. The phrase 'AI won’t replace the doctors, but those doctors will be replaced who don’t use Artificial Intelligence' suggests that rather than complete replacement, AI will support human roles, directly opposing the notion that AI will completely replace human teachers.


Input: Task: pass the claim using the given text. Claim: Natural environments can reduce stress and improve mental health. [SEP] Text: Despite this current policy discourse, little is actually known about the current organisation of crisis services in the UK, or the experiences of those accessing them [12]. A recent systematic review explored the currently available evidence on the organisation, experiences, effectiveness, and aims of crisis services for children and young people [13]. The review demonstrated a wide range in crisis services available globally, with many having positive effects on those that utilise them, and established three categories of organisation of crisis services; triage/assessment-only; digitally mediated support approaches; and intervention approaches and models [13]. This research aims to contribute to the growing field of research conducted on crisis mental health services, to help fill gaps identified within the field. The context of the current research is Greater Manchester, England, an area that has witnessed devolution of its health and social care budget, a process whereby power and funding is transferred from central to local government [14]. As a part of the devolution process, has made a significant investment into mental health services for children and young people, with a newly created Pathway, to offer a solution to the calls for better crisis service provision across the 10 localities of the city-region. In 2017, the Pathway was established in Greater Manchester, with the aim to improve the experiences of children and young people accessing crisis care services and avoid A&E admissions [1]. The pathway comprises six newly created and enhanced established services (see Table 1). Table 1 Crisis care pathway servicesFull size tableAs part of the Pathway’s plan, these crisis services should work together, and with wider mental health services in the community, to support young people on their path to wellness. A key intention of the current study is to examine the extent to which this aspiration has been realised in practice. Since the creation of the Pathway in 2017, these services have been slowly implemented across the 10 boroughs of and have evolved according to need. The information provided in Table 1 is the most relevant and up to date description of services as they currently stand. Methods of effective and consistent data collection were not designed into the implementation of the Pathway, making it difficult for managers to evaluate the effectiveness of this new crisis service delivery system. However, funders and managers of the Pathway wanted to evaluate this new pathway, so that services can continue to improve for the benefit of the young people accessing them. They asked the University of Manchester to conduct a third-party study to investigate this for them. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the organization and effectiveness of crisis mental health services in the UK, without addressing the specific impacts of natural environments on stress reduction or mental health improvement.


Input: Task: corroborate the claim using the given text. Claim: Horizontal gene transfer allows bacteria to acquire new traits. [SEP] Text: Consistent with previous findings that transferred transporters were enriched in Methanosarcina genomes (Garushyants, Kazanov & Gelfand, 2015), transporters were especially enriched in HGTs in our dataset: 15% of HGTs involved transporters of some kind compared to 5% in the whole dataset of all genomes. Indeed, transporters can be expected to confer immediate benefits to a cell after horizontal transfer. Figure 9: COG categories of genes shared between archaea and bacteria. (A) COG categories of all genes in all genomes, (B) all genes shared between bacteria and archaea as measured by RBHs, and (C) all genes identified as HGTs by DarkHorse. (D) Boxplot comparing COG cateogories that are enriched in HGTs. (E) Boxplot comparing COGs that are enriched in RBHs. In the boxplots, the lines represent the mean, points represent outliers, the edges of the box are the 25th and 75th percentiles and the whiskers represent the 90th percentile. Values in the boxplots are normalized by the appropriate total numbers of genes. Download full-size image DOI: 10. 7717/peerj. 3865/fig-9 Interestingly, archaea and bacteria share many genes in the Translation category, but these genes are not horizontally transferred (Fig. 9C). This is consistent with translation proteins being highly conserved between archaea and bacteria (Koonin et al. , 2012) and is likely an example of genes shared from vertical descent. and Metabolism genes are also frequently shared by archaea and bacteria but not horizontally transferred (Fig. 9C). Notably, Transcription and genes do not seem to be shared between bacteria and archaea (Fig. 9). The lack of shared genes in these categories is not surprising (Cordero & Hogeweg, 2009), considering that archaea and bacteria employ completely different transcription machinery (Jun et al. , 2011) and signal transduction pathways (Ulrich, Koonin & Zhulin, 2005). The abundance of shared genes in each COG category was normalized for genome size using the empirical fit log–logistic function (Table S6). As with the total dataset, temperature, oxygen utilization and GC content were all significantly correlated with the number of shared genes in many COG categories (Table 2). [SEP] Justify:

Output: The text corroborates the claim by discussing the enrichment of transporters in horizontal gene transfers (HGTs) in Methanosarcina genomes. It specifically states that 'transporters can be expected to confer immediate benefits to a cell after horizontal transfer,' which implies that horizontal gene transfer provides bacteria with new traits that enhance their capabilities.


Input: Task: contrast the claim using the given text. Claim: AI will fully replace human teachers in the next decade. [SEP] Text: Under this model, AI could be programmed to alert the healthcare provider on all the variables not considered in an algorithm, to help the healthcare provider explore to what extent the AI recommendations can be valuable in a specific context or with a specific patient. For instance, if an AI is recommending antidepressants for a patient who is also pregnant, it would alert the doctor that such medications aren’t yet tested in this population — allowing the doctor to consider other data points in deciding the next best step. To support this model — in which humans lead, but AI support — the AI-integrated future shouldn’t just focus on improving AI. An AI-augmented healthcare system must include healthcare worker training and support in both AI literacy and human intelligence literacy. Education can also focus on helping healthcare providers recognise when to question patterns; how to challenge predictions; and the value of trusting intuition — essentially building capacity to tolerate uncertainty. This future-protecting healthcare education would help reduce the risk of “automation bias,” whereby humans allow the AI to work autonomously and the algorithm is trusted, even in the face of clear evidence that it’s wrong. AI has given us a valuable gift: the opportunity to explore what aspects of human intelligence are critical in healthcare, and which tasks can be enhanced with technology. After all, both human brains and AI are wired for prediction, but humans have the power to interrogate, question and evaluate these predictions while AI has computing power beyond a human brain. Both are needed to manage the complexities of patient care. Michelle D. is the Director of the Centre for Education and of the Centre for Scholarship in at in Australia. She is an award-winning educator, having received the ‘Teaching Excellence’ award amongst others, and is the author of the “Effect: How to Survive and Thrive through the Unexpected“. Originally published under by 360info™. Enjoy this 2024. Here’s why. Focus on 2024 It’s a wonderful year for a Moon dance Hydrogen can revolutionise clean energy, transport, decarbonise industrial processes … and cook your dinner. Focus on 2024 Hydrogen makes itself at home The UK and US have both approved a gene editing therapy to overcome the genetic mutation that causes sickle cell disease, but the treatment is expensive. [SEP] Justify:

Output: The text contrasts the claim by discussing a model where AI serves as a supportive tool for human healthcare providers rather than replacing them. It emphasizes the importance of human intelligence and decision-making, stating that humans have the ability to interrogate and evaluate AI's predictions, which indicates a collaborative rather than a replacement role for AI. The emphasis on training healthcare workers in AI literacy further suggests that the future involves partnership, not complete replacement.


Input: Task: pass the claim using the given text. Claim: Natural environments can reduce stress and improve mental health. [SEP] Text: As there was no rigorous data that the team at the University of Manchester could access to evaluate the services, it was decided between NHS managers and the research team that a survey study would be conducted (between November 2022 and January 2023) with professionals working within crisis services in Greater Manchester, to compare their perspectives of crisis services with the original aims of the Pathway [1] and answer the following research questions: 1) How do professionals believe crisis services can be improved for young people in Greater Manchester? 2) What actions can crisis services take to improve their service provision? 2 Methodology2. 1 Aims & designThe aim of the current research was to explore how crisis mental health services for young people can be improved from the perspective of professionals. To achieve this, a brief online survey, including a mixture of quantitative, Likert scale items and qualitative, open-ended questions, was undertaken with professionals working within crisis mental health services for young people in Greater Manchester. The survey was designed to take no longer than 10 min to complete by participants, to consider their busy working schedules, and increase the likelihood of completion. 2. 2 Quantitative data generationParticipants were asked to evaluate current crisis service provision in through a set of 14 Likert scale questions. These questions were based on the original Pathway document [1] which set forth the aims of crisis services in Greater Manchester. The 14 statements were reviewed and confirmed by mental health service organisational leaders in the NHS as a reliable evaluation scale. Participants were asked, “To what extent do you agree with the following statements? ” The results of these questions are presented in three categories (“Agree,” “Neither,” “Disagree”). 2. 3 Qualitative data generationThe last section of the survey asked participants “How do you think crisis mental health services for young people could be improved? ”. The question also asked participants to consider “the services already available,” and “the NHS’s long-term plan” when responding. It was made clear that this was the final question of the survey and participants were asked to provide as much detail as possible in their response. The aim of including this information was to encourage participants to provide detailed responses. 2. 4 ParticipantsThe survey was distributed to professionals working within crisis services in Greater Manchester. [SEP] Justify:

Output: The text discusses a survey study focused on evaluating crisis mental health services for young people in Greater Manchester. There is no mention of natural environments or any evidence supporting the claim that such environments reduce stress or improve mental health. Therefore, the text is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Horizontal gene transfer allows bacteria to acquire new traits. [SEP] Text: 666 p = 0. 001 NS DOI: 10. 7717/peerj. 3865/table-2 have identified bacteria with unusually large numbers of shared genes with archaea after accounting for the effect that genome size has on the number of shared genes (Fig. 5A). In general, these unusually large numbers of shared genes can be explained by horizontal gene transfer from archaea to bacteria (Figs. 4 and 7). More specifically, (hyper)thermophilic and anaerobic archaea are most likely to transfer genes to bacteria that live in high-temperature and anoxic habitats respectively (Fig. 7), though the genes transferred between anoxic and high temperature archaea and bacteria do differ (Table 2). In contrast, aerobic mesophiles appear to engage in very little inter-domain horizontal gene transfer. The most likely explanation for these results is that the (hyper)thermophilic and anaerobic organisms whose genomes were included in this study were isolated from environments (e. g. , hot springs, oil wells, sediments) with high population densities where cells are in close proximity and therefore more likely to exchange genes. This study suggests that bacteria inhabiting bodies of water are less likely to contain genes transferred from archaea and that rates of horizontal gene transfer would be greatly underestimated if based only on aquatic organisms. Furthermore, we have demonstrated the importance of adjusting for genome size when investigating other factors associated with the number of genes shared among genomes. Due to this genome size adjustment, this study is the first to be able to examine the effect of environment on horizontal gene transfer between archaea and bacteria on a broad scale. 1-5 of data used in analyses DOI: 10. 7717/peerj. 3865/supp-1 from the upper 95% CI for shared genes split into : 10. 7717/peerj. 3865/supp-2 Figures 1–7 DOI: 10. 7717/peerj. 3865/supp-3 We would like to thank Devine for statistical advice and Cedar McKay for computer support. authors declare there are no competing interests. Clara A. Fuchsman, Collins and William J. Brazelton conceived and designed the experiments, performed the experiments, analyzed the data, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper. conceived and designed the experiments, wrote the paper, reviewed drafts of the paper. A. [SEP] Justify:

Output: The text corroborates the claim by explaining how horizontal gene transfer is responsible for bacteria acquiring new traits from archaea. It details the evidence found in the research that shows unusually large numbers of shared genes between bacteria and archaea, which can be attributed to horizontal gene transfer, particularly in specific environmental contexts. This is illustrated by the findings that hyperthermophilic and anaerobic archaea transfer genes to corresponding bacteria in high-temperature and anoxic habitats, thereby supporting the claim that horizontal gene transfer facilitates the acquisition of new traits by bacteria.


Input: Task: contrast the claim using the given text. Claim: Artificial intelligence systems can perfectly teach any subject without human supervision. [SEP] Text: . org 2024 in to your account Login or this option if you have an account on informs. org or if you want to become an member Combine personal and institutional access with an Informs PubsOnline account using main navigation't sign in? Forgot your username? Enter your email address below and we will send you your username If the address matches an existing account you will receive an email with instructions to retrieve your username Login to your account Login or this option if you have an account on informs. org or if you want to become an member Combine personal and institutional access with an Informs PubsOnline account using 3, 2023 in a Brain: of : Share onShare on PRINT 10. 1287/LYTX. 2023. 01. 12 Since its launch in November 2022, ChatGPT has been dubbed everything from “mind-blowing” (CNET) to the artificial intelligence (AI) industry’s “next big disrupter” (York Times) – and with good reason. The brainchild of applies machine-learning algorithms to OpenAI’s GPT-3. 5 family of large language models, fine-tuned with both supervised and reinforcement learning techniques, to interact conversationally with users in a way that sounds surprisingly humanlike. Using previous questions and answers to inform its next responses, ChatGPT is able to remember a dialogue thread in a way that sounds both creative and authoritative. It can also create content, generate AI art, write code and convert unstructured data into a structured format. Although not without its limitations – OpenAI readily admits that it sometimes provides plausible-sounding but incorrect answers and can often be excessively verbose – ChatGPT has already attracted a million users and led many experts to conclude that it poses a serious threat to Google. With the global chatbot market expected to exceed $10. 5 billion by 2026, ChatGPT clearly represents not only an incredibly powerful tool but a major leap forward in self-learning artificial intelligence. By its own admission (see sidebar), ChatGPT is not artificial general intelligence (AGI). Although its capabilities are most impressive, ChatGPT is really manipulating symbols without any understanding of what those symbols mean. And until that is possible – until today’s artificial intelligence advances to something that has the ability to actually understand any intellectual task that a human being can – AGI remains a hypothetical (although many would argue inevitable) possibility. [SEP] Justify:

Output: The text contrasts the claim by emphasizing that while AI systems like ChatGPT have advanced capabilities, they are limited in understanding and can sometimes provide incorrect answers. It specifically states, 'ChatGPT is really manipulating symbols without any understanding of what those symbols mean' and notes that 'AGI remains a hypothetical possibility.' This implies that AI cannot solely teach any subject perfectly without human oversight, as it lacks genuine understanding.


Input: Task: pass the claim using the given text. Claim: Natural environments can reduce stress and improve mental health. [SEP] Text: A gatekeeper at the NHS (Service), who acted as for the Pathway, was utilised to gain crisis professionals as participants in this study. This gatekeeper distributed the survey to relevant managers in crisis services, who then cascaded it to the professionals working in their respective teams. This snowballing distribution technique was useful for obtaining responses from different services which provide care for young people in crisis across Greater Manchester. The survey asked participants to state which crisis service they were affiliated to, so that the distribution of participants could be gauged. The options of services to choose from in the survey included; and In-reach and Safe Zones. These services were deemed to be the most relevant by the crisis service Programme Manager. However, “Other” was also provided as a response category, to reflect those who worked within other services providing crisis care for young people, such as A&E. There were 61 responses to the survey. However, 1 response did not record any data, so this was removed from the sample, leaving a total of 60 responses. The distribution of participants among services is reported in Table 2 below. Table 2 Crisis service affiliationFull size tableParticipants specific profession or role was not recorded in the survey, as this would increase the risk of identification of participants when linked to their service. This makes it difficult to ascertain if all roles within these services are represented in the sample. However, as relatively small teams, the number of participants in this study from the the Team, and is enough to represent the target population of the professionals working within these crisis services. Whereas for the Assessment & Inreach Centre, this sample is far from representative. Although still a small team, two participants is not representative of the professional workforce for this service. 2. 5 Analytic strategyQuantitative sections of the survey were used for descriptive purposes, with the qualitative section being the primary focus of this study. scale data from the survey focuses on the extent to which the key aims of mental health crisis services in were being realised. scale responses are presented through a stacked bar chart (Fig. 1), presented in the findings section of the paper, to clearly visualise aspects of crisis services which were perceived by participants as being in most need of improvement. Missing item level data is removed, with the percentage score of those who responded to the evaluation question reported. Fig. 1Likert scale statements and responsesFull size imageLikert scale statementsa. [SEP] Justify:

Output: The text provides detailed information about the methodology of a study concerning crisis services but does not address or support the claim regarding the benefits of natural environments on stress reduction and mental health. Instead, it focuses on the distribution of a survey among crisis professionals, which is unrelated to the claim.


Input: Task: corroborate the claim using the given text. Claim: Horizontal gene transfer allows bacteria to acquire new traits. [SEP] Text: Proceedings of the of Sciences of the of America 106:21748-21753 Danovaro R, Dell’. 2008. Major viral impact on the functioning of benthic deep-sea ecosystems. Nature 454:1084-1087 Dell’Anno A, Danovaro R. 2005. Extracellular DNA plays a key role in deep-sea ecosystem functioning. Science 309:2179. 2006. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Applied and 72:5069-5072 Frigaard N-. 2006. Proteorhodopsin lateral gene transfer between marine planktonic Bacteria and Archaea. Nature 439:847-850 Fuchsman CA, Rocap G. 2006. Whole-genome reciprocal BLAST analysis reveals that planctomycetes do not share an unusually large number of genes with eukarya and archaea. Applied and 72:6841-6844 Fütterer. 2004. Genome sequence of Picrophilus torridus and its implications for life around pH 0. Proceedings of the of Sciences of the of America 101:9091-9096. 2015. Horizontal gene transfer and genome evolution in Methanosarcina. BMC 15:102 é. 2005. Genome streamlining in a cosmopolitan oceanic bacterium. Science 309:1242-1245. 2015. No evidence of inhibition of horizontal gene transfer by –Cas on evolutionary timescales. 9:2021-2027 Guieysse B, Wuertz S. 2012. Metabolically versatile large-genome prokaryotes. in Biotechnology 23:467-473. 2015. Horizontal gene transfer in an acid mine drainage microbial community. BMC Genomics 16:496 Hirschler-Rea A. 2003. Isolation and characterization of spirilloid purple phototrophic bacteria forming red layers in microbial mats of Mediterranean salterns: description of Halorhodospira neutriphila sp. nov. and emendation of the genus Halorhodospira. of Systematic and 53:153-163. 2007. Alkalilimnicola ehrlichii sp. [SEP] Justify:

Output: The text supports the claim by mentioning multiple instances of horizontal gene transfer, specifically noting how it is significant in the context of microbial communities and evolutionary biology. For example, it references studies related to horizontal gene transfer in Methanosarcina, which implies that such processes are relevant to the acquisition of new traits in bacteria.


Input: Task: contrast the claim using the given text. Claim: Artificial intelligence systems can perfectly teach any subject without human supervision. [SEP] Text: But we can look at ChatGPT’s capabilities and limitations to conclude a number of interesting and useful things about the future of AI and the emergence of AGI. Many shortcomings of today’s AI that are impeding it from becoming AGI can be overcome. AGI’s emergence will be a gradual process rather than a “singularity. ” It will become progressively difficult to determine whether some future system is an AGI. What’s Needed for AGI To become an AGI, a system will need to add the ability to comprehend that physical objects exist in a physical environment – words are most useful if they represent objects, thoughts or ideas that exist in a reality. ChatGPT’s words exist only in the context of other words, not the abstract concepts they might represent. Further, there are many concepts that are difficult to express with words alone. Consider the difficulty of describing a work of art or music in words without a picture or recorded sound. This limitation can be overcome by adding multisensory inputs to an AI and, more importantly, an underlying data structure that supports creating relationships between multiple types of data. Physical objects have not only visible shapes and colors but textures and other tactile sensations, aroma, taste, known interactions with other objects, and a characteristic of persistence. Consider your understanding of a soap bubble. The words are just a shortcut for your multisensory understanding of its appearance, ephemeral nature, interaction with other bubbles and other physical objects, and a host of other sensations. To capture something akin to your understanding of the bubble, an AGI will require an internal mental model of its surroundings with the entity at its center, resembling the way in which humans view the world around us from our own point of view. How could a system understand or mimic the concept of a “point of view” without ever having experienced one? An artificial entity must also possess a perception of time, which allows for an understanding of future outcomes based on current actions. Finally, AGI will only be possible if the artificial entity has an imagination, which allows it to consider multiple possible actions, evaluate their potential outcomes and then choose the option that seems most plausible. Is this a complete list of capabilities needed for AGI? Of course not. But the implementation of these generic capabilities will lead us to a better understanding of what remains to be addressed on the road to AGI. [SEP] Justify:

Output: The text contrasts the claim by discussing the limitations of current AI systems like ChatGPT, emphasizing that these systems lack certain essential capabilities necessary for achieving Artificial General Intelligence (AGI). It argues that a system must comprehend physical existence, interactivity, and possess human-like qualities such as imagination and a sense of time, which current AI lacks. Thus, the claim that AI can perfectly teach any subject without supervision is rebutted by highlighting these shortcomings.


Input: Task: pass the claim using the given text. Claim: Natural environments can reduce stress and improve mental health. [SEP] Text: Crisis mental health services are delivered at a time that works for young peopleb. Crisis mental health services are delivered in a place which works for young peoplec. Crisis mental health services are delivered in a way which works for young peopled. Crisis mental health services are organized around young people and their needse. Crisis mental health services provide young people with the right amount of help for the right length of time to keep them safe and supportedf. Crisis mental health services are quickly available for young peopleg. Crisis mental health services are responsive and flexibleh. People working with young people in mental health crisis services are trained and supported so they feel confident to better help young people when they are strugglingi. Different services and agencies work together effectively to provide support for young people in mental health crisisj. Families and carers of YP in crisis are fully involved in their care, every step of the wayk. Movement between services is clear and well plannedl. Services are transparent and clear with young people in crisis about their carem. Mental health services for young people are effectiven. Mental health crisis services for young people are fully integratedAnalysis of the qualitative data collected in the survey builds on the key findings from the descriptive quantitative results, to understand professionals' perspectives on how improvements can be made to current crisis services offered in Greater Manchester. Qualitative data was subjected to inductive reflexive thematic analysis [22], using NVivo software to help with the coding process. The first author conducted the first three stages of the reflective thematic analysis process: data familiarisation, systematic data coding, generating initial themes. Two other co-authors were then involved in the remaining three stages of analysis: developing and reviewing themes, refining, defining and naming themes, and the report writing process. This was particularly helpful in the developing and reviewing stage, as during this stage codes and themes could be sense-checked against the supporting quotes from the raw data. Whilst interpretation is a key element of this method [22], it is key that themes are representative of the data collected. Once themes were developed from the qualitative data, these findings were used to gain a deeper understanding of participants responses to the quantitative section of the survey. 2. 6 Participant’s self-assessed knowledge of crisis serviceThe survey asked participants to rate their understanding of crisis services in Greater Manchester. [SEP] Justify:

Output: The text does not discuss natural environments or their impact on stress and mental health. Instead, it focuses on crisis mental health services for young people and their organization, delivery, and effectiveness. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Horizontal gene transfer allows bacteria to acquire new traits. [SEP] Text: Nov, a novel arsenite-oxidizing, haloalkaliphilic gammaproteobacterium capable of chemoautotrophic or heterotrophic growth with nitrate or oxygen as the electron acceptor. of Systematic and 57:504-512 -. 2004. Genome sequence of the deep-sea γ-proteobacterium Idiomarina loihiensis reveals amino acid fermentation as a source of carbon and energy. Proceedings of the of Sciences of the of America 101:18036-18041. 2001. High guanine-cytosine content is not an adaptation to high temperature: a comparative analysis amongst prokaryotes. Proceedings of the B: 268:493-497. 2003. Horizontal gene transfer accelerates genome innovation and evolution. and Evolution 20:1598-1602 Jun S-. 2011. Archaeal RNA polymerase and transcription regulation. in Biochemistry and 46:27-40 Kanhere A, Vingron M. 2009. Transfers in prokaryotes show differential p2001. Archaeal dominance in the mesopelagic zone of the Pacific Ocean. Nature 409:507-510. 2011. Networks of gene sharing among 329 proteobacterial genomes reveal differences in lateral gene transfer frequency at different phylogenetic depths. and Evolution 28:1057-1074. 2012. Phylogenomics of prokaryotic ribosomal proteins. 7:e36972. 2002. SHOT: a web server for the construction of genome phylogenies. Trends in Genetics 18:158-162 Lawrence JG, Hendrickson H. 2003. Lateral gene transfer: when will adolescence end? 50:739-749. 2012. Nitrospira-dominated biofilm within a thermal artesian spring: a case for nitrification-driven primary production in a geothermal setting. Geobiology 10:457-466. 2010. High frequency of horizontal gene transfer in the oceans. Science 330:50 Meyer-. 2011. Hydrothermal ecotones and streamer biofilm communities in the. 13:2216-2231 Molin S, Tolker-Nielsen T. 2003. Gene transfer occurs with enhanced efficiency in biofilms and induces enhanced stabilisation of the biofilm structure. in Biotechnology 14:255-261 ø -Valera F. 2005. [SEP] Justify:

Output: The text corroborates the claim by stating that 'Horizontal gene transfer accelerates genome innovation and evolution.' This statement directly supports the claim that horizontal gene transfer enables bacteria to acquire new traits by promoting innovation and change in their genomes.


Input: Task: contrast the claim using the given text. Claim: Artificial intelligence systems can perfectly teach any subject without human supervision. [SEP] Text: These AGI concepts are not impossible to create but require a mind shift in our approach to AI. Starting with a text-based system like ChatGPT and attempting to extend it to handle multisensory information, a mental model, cause and effect, and the passage of time is a daunting prospect. But starting with a data structure and set of algorithms to handle this diverse information and extending them to the text abilities of GPT with the vision, planning and decision-making of an autonomous robot is a much more promising approach. AGI vs. the When considering the likelihood of such a system, understand that the human brain does all these things in an organ that weighs about 3. 3 pounds and uses about 12 watts of energy. We know a lot about the brain’s structure and the way its neurons work but have yet to fill in the complete picture. Biological neurons function differently from the “perceptrons” of today’s neural networks at a basic level, and this accounts, in part, for the unparalleled energy efficiency of the brain. We do know that the initial structure of the brain is defined by our DNA, and the complete human genome is only about 750 MB. What fraction of our DNA defines the brain? We don’t know because the structure of any human part is largely dependent on its chemistry, and we have a much better idea of how DNA applies to chemistry than about how it applies to structure. But somehow, the DNA defines the structure of a person, which includes the structure and chemistry of the brain. Once the brain is “turned on,” its structure immediately begins to modify itself to handle the data and experiences it receives. We can presume, though, that generalized intelligence is a direct outgrowth of the structure that is defined by our DNA. The neocortex is the part of the brain humans use to think. Maybe its structure is defined by only 1% of that DNA, maybe 10%. Again, we really don’t know, but that means we might be able to define a complete AGI in a program that is as small as 7. 5 MB. And 7. 5 MB is a program that is well within the scope of a research team to write in just a few years. Thus, the AGI problem is really what is going to be written, not what the underlying structure requires gigabytes to define. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexities and limitations of creating advanced artificial general intelligence (AGI) systems. It highlights that while AGI concepts are achievable, they require significant advancements beyond current text-only models like ChatGPT. The text emphasizes the differences between human brain function and current AI technology, suggesting that a complete understanding and emulation of human thought processes in AI is still a daunting task, thus implying that AI cannot perfectly teach any subject without human supervision.


Input: Task: pass the claim using the given text. Claim: Natural environments can reduce stress and improve mental health. [SEP] Text: Table 3 displays the survey results of the crisis services knowledge self-assessment. In summary, the survey demonstrates that only 15% of participants considered to have a “full understanding” of how the whole crisis support system for young people works, with 50% stating they had “some knowledge” about the whole crisis support system. Almost 27% of participants stated they know how “other services linked to my service” supports crisis care for young people, and a further 8% reported they only had “knowledge about how the service they worked within” supports young people in crisis. These findings clearly highlight a perceived lack of knowledge among professionals about the support crisis services provide in Greater Manchester, with 85% of participants declaring to not have a full understanding of said services. Table 3 Self-assessed crisis service knowledgeFull size table2. 7 FindingsThe full results of the surveys Likert scale questions are displayed in Fig. 1. Whilst the results of the Likert scale questions indicated that there was room for improvement across all evaluative measures, there were some areas that were reported to be in more need of improvement than others. A minimum threshold of 20% (with a 1% leeway under) was deemed as significant because this would mean that 1 in 5 professional staff were negatively reporting on an evaluation measure. There were 6 statements which reached the threshold of negative responses, demonstrated by participant selection of “Disagree” to the evaluation question. Figure 1 suggests that crisis services for young people in require improvement in the following areas: Being delivered at a time that works for young people (19. 23%); providing young people with the right amount of help for the right amount of time (19. 23%); providing crisis services which are quickly available (24. 53%); for different services and agencies to work together effectively (19. 23%); clear and well-planned movement between services (37. 25%); and for services to be fully integrated (26%). These findings clarify professionals’ perspectives about what aspects of current crisis services offered in can be improved. The following reflexive thematic analysis of the qualitative survey data utilises these key findings from the quantitative data to examine the possible reasoning’s behind the 6 key areas of improvement identified and discuss how crisis services may be able to resolve these identified issues. 2. [SEP] Justify:

Output: The text discusses survey results related to the knowledge and perceptions of crisis services among professionals, but it does not address the claim regarding natural environments and their effect on stress and mental health. Therefore, the text is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Horizontal gene transfer allows bacteria to acquire new traits. [SEP] Text: The genome of Salinibacter ruber: convergence and gene exchange among hyperhalophilic bacteria and archaea. Proceedings of the of Sciences of the of America 102:18147-18152. 2002. Aerobiosis increases the genomic guanine plus cytosine content (GC%) in prokaryotes. Journal of 55:260-264 Nelson-. 2012. Acquisition of 1,000 eubacterial genes physiologically transformed a methanogen at the origin of Haloarchaea. Proceedings of the of Sciences of the of America 109:20537-20542 Nelson--Chávez önheit. 2015. Origins of major archaeal clades correspond to gene acquisitions from bacteria. Nature 517:77-80 Podell S, Gaasterland T. 2007. DarkHorse: a method for genome-wide prediction of horizontal gene transfer. 8 2008. A database of phylogenetically atypical genes in archaeal and bacterial genomes, identified using the DarkHorse algorithm. BMC Bioinformatics 9:419. 2006. Viruses of the Archaea: a unifying view. Microbiology 4:837-848. 2016. Abundances, diversity and seasonality of (non-extremophilic) Archaea in Alpine freshwaters. Leeuwenhoek, of General and 109:855-868. 2011. Differences in lateral gene transfer in hypersaline versus thermal environments. BMC 11:199 Schippers A, Kock D, Höft C, Köweker G, Siegert M. 2012. Quantification of microbial communities in subsurface marine sediments of the black sea and off namibia. Frontiers in Microbiology 3 2011. Harvesting evolutionary signals in a forest of prokaryotic gene trees. and Evolution 28:1393-1405. 2009. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and 75:7537-7541. 2011. Ecology drives a global network of gene exchange connecting the human microbiome. Nature 480:241-244. 1999. Genome phylogeny based on gene content. 21:108-110. 2003. The COG database: an updated version includes eukaryotes. BMC Bioinformatics 4:41. 2005. [SEP] Justify:

Output: The text provides multiple pieces of evidence regarding gene exchange and the impact of horizontal gene transfer on bacteria and archaea, such as 'acquisition of 1,000 eubacterial genes physiologically transformed a methanogen' and the mention of research on 'differences in lateral gene transfer.' These statements support the claim that horizontal gene transfer enables bacteria to gain new traits.


Input: Task: contrast the claim using the given text. Claim: Artificial intelligence systems can perfectly teach any subject without human supervision. [SEP] Text: At this point, we simply don’t know what to write as the fundamental AGI algorithm. The massive computer programs of today’s AI might not even be necessary for AGI. emergence of AGI is likely to be gradual rather than all at once because advances in AGI development will create solutions or capabilities that will be individually marketable. Consider how adding a generic mental model would enhance any mobile system, such as an autonomous robot or self-driving car. Consider how improving language skills has already revolutionized personal assistants and online search. Consider how understanding the interactions of things will improve system decision-making. All these capabilities already exist at some level. As they are merged and each advances at its own rate, systems will approach or exceed human-level ability in some areas and others will lag behind. Today’s AI has superhuman capabilities in some areas and can’t match the abilities of most 3-year-olds in others. This situation will continue, and AI will advance sporadically in different areas – who is to say a system that (for example) can pass graduate-level exams in many areas but can’t make a cup of coffee is a “general intelligence” or not? Impeding long-term AGI development is the commercial need for short-term results. Take, for example, the current state-of-the-art computer vision used in self-driving cars, which is generally inadequate for safety. To solve this problem, the vision of self-driving cars is augmented with other sensors (radar, lidar, ultrasound, etc. ) that provide more absolute information about the car’s surroundings. Even though this represents a great solution to optical vision in self-driving cars, it may or may not contribute to advancing an overall AGI system. The additional sensors, in fact, may “solve” the present problem in a way that relegates improvements to the underlying vision system to the back burner. We Won’t have widely varying levels of ability. test has long been an exemplar for general intelligence, but as systems like ChatGPT get closer to human-level language abilities, the goalposts need to be moved. It is clear that for ChatGPT to pass a Turing test, it would have to be reprogrammed to lie about its own abilities and limitations – not a desirable outcome. [SEP] Justify:

Output: The text contrasts the claim by suggesting that while AI systems may have superhuman capabilities in certain areas, they are not universally competent and can lag behind human abilities in many others. It argues that AI development is sporadic and dependent on commercial needs, indicating that perfect teaching without human supervision is not achievable with current technology. Additionally, it emphasizes that passing exams does not equate to general intelligence, which counters the notion of AI's perfect teaching ability.


Input: Task: pass the claim using the given text. Claim: Natural environments can reduce stress and improve mental health. [SEP] Text: 8 Qualitative themesResults from the thematic analysis of the qualitative survey questions are displayed in Table 4 as super-ordinate themes; the challenges of navigation, issues of accessibility into and between services, and the need to improve integration, alongside their respective sub-ordinate themes. Table 4 Super-ordinate & sub-ordinate themesFull size table2. 9 The challenge of navigationThe first super-ordinate theme discussed, which presented a significant problem to current mental health crisis services for young people was the challenge of navigation. It is clear from survey responses that navigating crisis services was an issue faced by both service users and staff working within crisis services. “The interface working within crisis mental health services for young people can be confusing and challenging to navigate. It is not always clear what the roles and responsibilities of the professionals involved from children's services are…” (Participant 34, Liaison) The confusion about who does what makes navigating crisis services a challenge for those working within crisis services and for those trying to access them. 2. 9. 1 InconsistencyAn inherent factor contributing to the challenge of service navigation is the inconsistency in crisis service provision across Greater Manchester, with one response noting how, “vary across locality. ” (Participant 23, Safe Zones). Not only does this lead to difficulties in navigating services, but also inequalities, with another response stating, “some areas have greater resources than others, which can be a barrier when promoting young people’s social and mental wellbeing. ” (Participant 5, Team). 2. 9. 2 Overreliance on A&EFrom the lack of consistency in offer of crisis services, it is unsurprising that many young people in crisis will be directed to A&E as a consistent offer regardless of location, despite this being perceived as an undesirable destination for young people experiencing mental health crisis. “My main worry is A&E departments, lots of children, young people and parents are directed to A&E in a crisis however that kind of environment for a person experiencing a mental health crisis is not appropriate in my opinion. ” (Participant 43, Safe Zones) Survey responses suggested that there was an overreliance on A&E, even for those registered to other mental health services, due to current gaps in crisis service provision, particularly out of hours. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the challenges of navigating mental health crisis services for young people and the inconsistency in service provision. It does not mention natural environments or their impact on stress reduction and mental health improvement.


Input: Task: corroborate the claim using the given text. Claim: Fossil records provide evidence for evolutionary changes. [SEP] Text: Plastid phylogenomics and fossil evidence provide new insights into the evolutionary complexity of the ‘woody clade’ in access Published: 12 April 2024 Plastid phylogenomics and fossil evidence provide new insights into the evolutionary complexity of the ‘woody clade’ in Jia1 na1, Shuying Wang1 na1, Jinjin Hu1 na1, Ke Miao1,2, Yongjiang Huang1 & …Yunheng Ji1 Show authors BMC 104. 79 and 100. 23 Ma), leading to the origin of the stem lineage ancestors of Altingiaceae, Cercidiphyllaceae, Daphniphyllaceae, and Hamamelidaceae within a very short time span (∼4. 56 Ma). Compared with the tree topology recovered in a previous study based on nuclear genome data, cytonuclear discordance regarding the interfamilial relationships of the WCS was detected. ConclusionsMolecular and fossil evidence imply that the early divergence of the WCS might have experienced radiative diversification of crown groups, extensive extinctions at the genus and species levels around the Cretaceous/Paleocene boundary, and ancient hybridization. Such evolutionarily complex events may introduce biases in topological estimations within the WCS due to incomplete lineage sorting, cytonuclear discordance, and long-branch attraction, potentially impacting the accurate reconstruction of deep relationships. reports BackgroundThe core task of plant phylogenetics is to recover the tree of life for Plantae [1,2,3]. Although recent molecular phylogenetic studies have greatly improved our understanding of the angiosperm tree of life, some nodes remain notoriously recalcitrant [4,5,6,7,8]. Notably, the taxonomic affinities of such phylogenetically recalcitrant lineages have been markedly debated among previous morphology-based classification systems [e. g. , 9, 10–14]; and in recent molecular phylogenetic studies, the relationships between these nodes and related taxa were either poorly resolved or significantly incongruent [e. g. , 2, 7, 15–17]. Several lines of evidence suggest that these phylogenetically recalcitrant nodes may have undergone some evolutionarily complex events, such as radiative diversification, morphological convergence, and ancient hybridization, which most likely resulted in the absence of synapomorphies and/or phylogenetic conflicts inferred from different datasets [e. g. [SEP] Justify:

Output: The text corroborates the claim by discussing how fossil evidence provides insights into the evolutionary complexity of plant lineages, particularly in the context of the woody clade. It states that 'molecular and fossil evidence imply...' which indicates that fossil records are being used to understand and provide evidence for evolutionary changes in specific plant groups.


Input: Task: contrast the claim using the given text. Claim: Artificial intelligence systems can perfectly teach any subject without human supervision. [SEP] Text: Given that, a few alternatives have been suggested, such as the “coffee test,” “robot college test” and “flat pack furniture test. ” Taken together, these attempts at tests show our limited understanding of the nature of general intelligence itself. Furthermore, there are many people who could not pass various tests because of physical or cultural differences but otherwise seem to be generally intelligent. And none of these tests seem to address some questions that most children are good at, such as “what will happen next? ” But even with these tests, where would we place a system that can pass the robot college test but is too clumsy to make a cup of coffee? This means that we will continue to argue about whether AGI has been achieved for perhaps a decade after credible experts begin saying that it has been reached. By that time, systems will have surpassed human abilities in so many areas that we will be forced to agree that some sort of AGI has been created. AGI is Inevitable and As we learn more and more about brain function, the only argument against the eventual creation of AGI is that the human mind contains some fundamental “magic” that is outside the scope of physical systems, which we can replicate in nonbiological systems. That position aside, if all of today’s more specialized, individually marketable AI systems were built on a common underlying data structure, they could begin to interact with each other, building a broader context that can actually understand and learn. As these systems become more advanced, they will be able to work together to create a more general intelligence that approaches the threshold for human-level intelligence, then equals it, and eventually surpasses it. Perhaps only then will we humans begin to acknowledge that yes, maybe AGI does exist. It is inevitable because market forces eventually will prevail. All we are waiting for are the insights needed to make it work. When will that happen? Some experts say it will take hundreds of years before we know how the brain works, what its algorithms are and what its capacity is, but I would suggest that it is only a matter of time before we shift from our current dependence on bigger and bigger data sets and recognize that to approach true understanding, we must address the brain knowledge gap. Me to ChatGPT: Are you an AGI? ChatGPT: No, I am not an AGI. [SEP] Justify:

Output: The text contrasts the claim by emphasizing the limitations of current artificial intelligence systems, indicating a lack of understanding of general intelligence and acknowledging that even tests aimed at evaluating AI capabilities do not capture all necessary skills. The mention of various tests, such as the 'coffee test' and 'robot college test,' suggests that while advanced AI may surpass human abilities in some areas, it still requires further development and understanding of human intelligence. Hence, AI cannot yet perfectly teach any subject without human oversight.


Input: Task: pass the claim using the given text. Claim: Natural environments can reduce stress and improve mental health. [SEP] Text: “Most young people in care and who are under the care of CAMHS are experiencing self-harm/suicidal thoughts in the evening and during night time and carers/young people feel that currently crisis support does not meet their needs which leads to repeated A&E attendances and by the time MHL practitioner review the young person the crisis has reduced. This however creates a reliance on accessing A&E and leads to potentially unhelpful admissions. ” (Participant 21, Other) Gaps in current crisis services provision may have contributed to participants negative responses to the first and sixth Likert scale questions. 19. 23% of participants disagreed with the first statement (see Fig. 1a) which asked participants if they agreed that services were delivered at a time that works for young people. A further 24. 53% of participants disagreed with the sixth statement (see Fig. 1f) when asked if services were quickly available. If a young person reaches crisis point in the evening the quickest access to professional support is through attending A&E if specialist crisis mental health services are not available. However, it was suggested that rather than attending A&E, young people in crisis should be attending services which are appropriate for their needs. “I feel there needs to be a safer, more suitable place for anyone who is struggling with their mental health. This needs to be suited to a variety of needs and have the correct support for the people who are accessing it, by this I mean staff that are appropriately trained to support the people who turn up and also to have support for the staff that are providing this service. ” (Participant 43, Safe Zones) 2. 9. 3 24/7 crisis service provisionA suggestion was made across several survey responses, that may help resolve the current overreliance on A&E and provide a solution to the negative responses to the first (see Fig. 1a; services are delivered at a time that works for young people) and sixth (see Fig. 1f; services are quickly available) statements from the quantitative section of the survey. This suggestion was the implementation of 24/7 crisis service provision. The desire for 24/7 provision of young people’s crisis services amongst participants was strong, whether an overreliance on A&E was identified in participants responses or not. But for others, this was identified as a direct solution. [SEP] Justify:

Output: The text does not address the claim regarding natural environments and their impact on stress and mental health. Instead, it discusses the inadequacies of crisis support for young people, focusing on the reliance on A&E services and suggestions for improving mental health support services. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Fossil records provide evidence for evolutionary changes. [SEP] Text: , 4, 18–20]. The “woody clade” in Saxifragales (WCS), as defined by Jian et al. [21], comprises four woody families exclusively occurring in the Northern Hemisphere, i. e. , Altingiaceae (one genus, eight species) [22], Cercidiphyllaceae (one genus, two species) [23], Daphniphyllaceae (one genus, 30 species) [24, 25], and Hamamelidaceae (27 genera, 120 species) [7, 26]. The WCS represents one of the phylogenetically recalcitrant nodes in the angiosperm tree of life. The taxonomic affinities of these four families (as shown in Tables 1 and 2) are also contentious in the morphology-based classification systems proposed by Hutchinson [10], Cronquist [11], Dahlgren [12], Thorne [13], and Takhtajan [14]. This suggests a lack of robust morphological synapomorphies that unite them [21, 27]. Although previous studies have successfully recovered the phylogenetic backbone of Saxifragales and consistently resolved the WCS as a monophyletic group with strong support [8, 21, 27,28,29,30,31,32,33], the unresolved interfamilial relationships for Altingiaceae, Cercidiphyllaceae, Daphniphyllaceae, and Hamamelidaceae continue to be a subject of debate. Theoretically, the inconsistencies regarding the deep relationships of the WCS imply that it might have been subject to some evolutionarily complex events during its early evolution [16, 17, 19]. Table 1 Comparison of the order-level taxonomic placements of the four families within the “woody clade” in Saxifragales among previous morphology-based classification systemsFull size tableTable 2 Taxonomic studies of HamamelidaceaeFull size tableGiven that fossils represent the remains of past plants, they have the capacity to unveil intermediate evolutionary connections from the geological past, thereby offering valuable evidence for comprehending the evolution of the tree of life [34,35,36,37]. The combination of molecular and fossil evidence is recommended as an efficient approach for inferring the evolutionarily complex events that might result in phylogenetic recalcitrance in the angiosperm tree of life [16, 30, 38, 39]. [SEP] Justify:

Output: The text corroborates the claim by stating that fossils represent the remains of past plants and have the capacity to unveil intermediate evolutionary connections from the geological past, thereby offering valuable evidence for comprehending the evolution of the tree of life. This indicates that fossils are indeed a crucial component in understanding evolutionary changes.


Input: Task: contrast the claim using the given text. Claim: Artificial intelligence systems can perfectly teach any subject without human supervision. [SEP] Text: Whether the term is positive or negative in terms of strategic messaging and impact is outside the scope of this paper. “AI for good” has become a hallmark for the Unit (UN ITU) in particular. The UN has built a digital platform around the term, which is designed to encourage discussions and projects aimed at finding practical solutions for the UN’s Goals (SDGs) through AI [84]. The term “AI for good” then, in this context, refers to AI systems that help solve previously identified, complex global issues for society, thus benefiting humankind [78]. Those working to develop AI for good measure their success by their AI systems’ ability to help society reach certain goals. 2. 3 Beneficial AIAnother popular term, initially promoted more by the research community than by governments, is “Beneficial AI. ”“Beneficial AI” was spearheaded through the Future of Life Institute’s on Beneficial AI. This conference also yielded one of the very first sets of AI Principles, the Asilomar AI PrinciplesFootnote 3 which were signed by 5720 people, including 1797 AI and robotics researchers. Given the principles described in the document, the term initially appears to have had a close connection to technical AI research. In particular, it referred to topics that fall under the research field of AI safety [4, 16, 48], as well as topics related to the long-term future. Footnote 4 Outside of this research space, the term has been co-opted to broadly reference AI systems that benefit society and the environment, while avoiding definable and undefinable harm. 2. 4 Responsible AIA fourth commonly used term is “responsible AI. ” While the previously mentioned terms refer mainly to AI systems, “responsible AI” more often refers to the actions, and actors, involved in developing and deploying those systems. “Responsible AI” seems a more sophisticated term, perhaps due to the general connotations of “responsibility. ” It has been used to refer to many of the mechanisms or methods by which it could feasibly be achieved, such as responsible design and development for AI [7, 24]. It seems this term most often refers to processes that result in technical achievement and meet certain standards of responsibility. Some actors, particularly industry actors, likely feel that this term is more precise than terms that invoke ethics. [SEP] Justify:

Output: The text contrasts the claim by discussing various concepts surrounding AI, including 'AI for good' and 'responsible AI'. It highlights that AI systems are intended to benefit society and meet certain standards of responsibility, suggesting that the effectiveness of AI is evaluated based on its ability to help achieve societal goals rather than their capability to teach independently without human oversight.


Input: Task: pass the claim using the given text. Claim: Natural environments can reduce stress and improve mental health. [SEP] Text: “I feel some services may need to be 24/7 in order to prevent people attending A&E. ” (Participant 43, Safe Zones) However, it was conceded that for the delivery of 24/7 provision to be possible, investment would be needed; “Improved investment to meet the 24/7 aim. ” Other participants provided more detail about how 24/7 crisis service provision could be achieved, through redistribution of current resources. “I think the 24 hour offer could be covered using a rotation of staff from across the crisis pathway, bolstered by a robust out of hours referral process in liaison with trust helplines and Liaison services. ” (Participant 19, ) The next two super-ordinate themes, Issues of accessability into and between services, and How to improve integration, will contain more suggestions which may provide resolutions to this challenge. 2. 10 Issues of accessibility into and between servicesThe second super-ordinate theme to be discussed is that of issues of accessibility into and between services. Access follows on from the previous super-ordinate theme of The challenge of navigation, with elements of this theme linking closely to the challenges previously discussed. The sub-ordinate themes discussed in this section demonstrate the challenges currently faced surrounding accessibility of crisis services in Greater Manchester, and some potential solutions developed from analysis of survey responses. 2. 10. 1 Transition of careThe eleventh statement (see Fig. 1k) from the quantitative data collected in the survey received the most negative response, with 37. 25% of participants disagreeing with the statement that “movement between services is clear and well planned”. Participant responses to the qualitative section of the survey help develop an explanation for the poor response rate, highlighting several issues with the transition of care between services, affecting the accessibility of services. One of the major challenges identified was the transition to adult services for young people aged 16–18, creating another gap in service provision and leaving those in this age range in a precarious position. “I believe currently long-term support is proving to be a bit more difficult such as HITT not taking ages from 16+ and then miss communication from Adult services, stating they will not take anyone till they are 18, this is leaving some YP without any support. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the accessibility of crisis services and the challenges faced in transitioning care without addressing natural environments or their impact on stress and mental health. The emphasis is on service provision and accessibility issues in healthcare rather than on the therapeutic effects of natural environments.


Input: Task: corroborate the claim using the given text. Claim: Fossil records provide evidence for evolutionary changes. [SEP] Text: Recently, genome-scale sequence data, particularly plastid genomes (plastomes), have been increasingly used to solve historical puzzles in plant phylogenetics [e. g, 8, 28, 29, 40–48]. In general, phylogeny inferred from uniparentally inherited plastomes reflects only the maternal (or, in some cases, paternal) relationships, as compared to the more comprehensive evolutionary history recovered through the phylogenetic analyses of biparentally inherited nuclear genomes [49]. Nevertheless, the comparison of tree topologies inferred from plastomes and nuclear genomes can facilitate the determination of phylogenetic discordance between plastid and nuclear datasets (cytonuclear discordance), providing robust evidence to infer whether the evolution of the taxa in question has involved evolutionarily complex events, such as incomplete lineage sorting and hybridization [50, 51]. Recent phylogenomic studies have yielded valuable insights into the deep relationships within the WCS. Based on nuclear genome data generated by target-capture sequencing and RNA-seq, Folk et al. [28] recovered the phylogenetic backbone of the WCS with high-resolution and well-supported interfamilial relationships. In contrast, previous plastome-based phylogenetic analyses of the WCS taxa have demonstrated tree topologies with low support [52, 53] and inconsistent inter-familial relationships [32, 33]. Consequently, the family-level maternal relationships within the WCS remain ambiguous, providing weak evidence for detecting cytonuclear discordance in the deep relationships within the WCS. Notably, the maternal inheritance of plastomes in the WCS as well as in the Saxifragales has been verified by the investigations of several species including Hamamelis virginiana, Heuchera micrantha, and Tolmiea menziesii [54, 55]. By expanding the taxonomic sampling of the WCS to include the majority of genera, the objectives of this study are to recover a robust maternal backbone phylogeny of the WCS through analysis of plastome sequence data. Based on a time-calibrated phylogenetic framework, fossil evidence, and a comparison of plastome (this study) and nuclear [28] phylogenies, evolutionarily complex events putatively responsible for the phylogenetic recalcitrance of the deep phylogeny of the WCS were inferred. [SEP] Justify:

Output: The text supports the claim that fossil records provide evidence for evolutionary changes by discussing how fossil evidence is used alongside phylogenetic analysis to infer evolutionary relationships. It mentions that 'fossil evidence' is part of the study's framework, which aids in inferring 'evolutionarily complex events' responsible for the phylogenetic history. This implies that fossils are integral in understanding evolutionary changes, thereby corroborating the claim.


Input: Task: contrast the claim using the given text. Claim: Artificial intelligence systems can perfectly teach any subject without human supervision. [SEP] Text: It may be a preferable term from a communications perspective as it, similar to “trustworthiness,” 3. 1. a. The risk of misinterpretation or misuse is even higher when “trustworthy AI” is reused, amended and adopted in international policy contexts without the original relation to the three pillars and their corresponding requirements, or with only partial reference to them. The wide adoption of the term runs the risk of diluting its meaning beyond recognition and backfiring on serious policy efforts, by way of losing both the original intent and the core content the terminology is meant to encourage after all. 4. 1 Come hell or waters high: is this trustworthy AI? This subsection highlights some initial concerns around the term “trustworthy AI. ” It proposes two overarching concerns. First, various meanings of the term, depending on actor and context, can easily get conflated, effectively creating different meanings and understandings which can mislead. Second, the term could easily be ‘washed out’ of its original meaning through repetition,Footnote 7 whether or not this is the underlying intent from a strategic and self-interested perspective of an agent. In short, one concern is with the word “trustworthy” itself, another with the repeated usage of the word and its associated definition. This creates the backdrop for the subsequent review in Sect. 4. 2. , which examines the dissemination of the term and how it has seemingly been re-used in various political contexts, as well as the results of that usage. 4. 1. 1 a. ConflationThe term “trustworthy AI” conflates at least five meanings: trust in the proper functioning and safety of the technology; the technology being worthy of the trust of the humans making use of it or encountering it otherwise; humans making use of it or encountering it seeing the technology as trustworthy; humans making use of it or encountering it experiencing the technology as trustworthy; the technology that is worthy of trust to all. What does “trustworthy” mean in different contexts and to different actors? It is questionable whether any technology can even be trustworthy, given that this is a concept predominantly applied to human–human interactions [13]. More specifically, the term is typically applied to interactions in which we cannot be certain of the intentions of another person, but we assume they are innocuous based on the person’s past actions and other social signals [49]. [SEP] Justify:

Output: The text contrasts the claim by addressing concerns about the term 'trustworthy AI' and questioning the efficacy and reliability of AI systems. It suggests that the term 'trustworthy' may not even be applicable to technology, as it is typically associated with human interactions, implying that AI systems may not be able to teach perfectly without supervision due to these reliability concerns.