Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: Table 3 provides insights into the impact of synthetic data over different architectures, including bidirectional recurrent neural network (BRNN), convolutional neural network (CNN), and self-attention network Transforemer-based (Vanilla) referred to as (GEC-Trans), as same as two common synthetic data generation techniques: Grundkiewicz, Junczys-Dowmunt & Heafield (2019), and Pattern-POS Choe et al. (2019). BRNN with an attention mechanism designed to focus on nearby words achieved an F1 score of 49. 17 and a BLEU score of 62. 07. Furthermore, GEC-CNN with an attention mechanism offers the advantage of parallel training without the need for sequential operations. This CNN architecture seamlessly merged feature extraction and classification into a single task, this approach led to an improvement in the F1 score (+8. 57) and BLEU score (+9. 93). We also investigated the baseline GEC-Trans, a model built upon a modified version of the Transformer architecture, allowing it to process the entire input sequence simultaneously, which achieved F1 score of 68. 30 and BLEU score of 74. 33. On the other hand, we investigate the reliability of InSpelPOS over two state-of-the-art confusion methods Inverted-Spellchecker and Pattern-POS. Inverted-Spellchecker aims to generate confusion sets considering only spelling errors which reported 60. 66 and 72. 82 for F1 score and BLUE scores, respectively. However, pattern and POS-based methods generate synthetic errors utilizing a dictionary of common edits from monolingual data, and introducing noise in verbs, nouns, and prepositions. This technique reported 64. 73 F1 score and 73. 43 BLUE score which is better as compared to Inverted-Spellchecker and behind our proposed InSpelPOS. These results underscore the effectiveness and reliability of the semi-supervised method for constructing training data in the context of Indonesian GEC and address the challenge of limited training data availability. Table 3: Performance evaluation of GEC models for automated Indonesian text error correction including GEC--CNN, and GEC-Trans (Vanilla) that were trained using our synthetic data (InSpelPOS), and two common State-of-the-Art confusion techniques: OS. Recall F1 score -BRNN + InSpelPOS 56. [SEP] Justify:

Output: The text is irrelevant to the claim regarding semantic memory's role in understanding meanings. Instead, it focuses on the performance evaluation of various automated models for text error correction in Indonesian, discussing their architectural details and performance metrics without addressing semantic memory.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: Bilayered chitosan tube that comprises an outer layer of chitosan film and an inner layer of chitosan nonwoven nano/microfiber mesh. Nerve regeneration in chitosan tubes, on which the peptide was immobilized, exhibited efficacy similar to that of the isograft and represented a promising candidate for promoting peripheral nerve repair (202). It was reported that the chitosan nano/microfiber mesh tubes with a deacetylation rate of 93% had sufficient mechanical properties to preserve tube space, provided a better scaffold for cell migration and attachment, and facilitated humoral permeation to enhance nerve regeneration. As a result of fiber orientation, the tensile strength along the axis of the sheet increased (203). cells aligned along the nanofibers, oriented fibrous sheets could exhibited a Schwann cell column, thus functional and electrophysiological recovery occurred in time in the oriented group as well as in the bilayered group. Furthermore, histological analysis revealed that the sprouting of myelinated axons occurred vigorously followed by axonal maturation in the isograft, oriented, and bilayered group in the order (204). In addition, the applications of nanomaterials in bladder and blood vessel tissue engineering have been reported (205, 206). In summary, at present, although there are many problems, we believe that nanomaterials are very important in tissue engineering fields in the future. Summary and perspectiveOver the last ten years, there have been substantial developments in nanomedicine. Building upon these advances, much work needs to be done over the next 5 to 10 years to more fully realize the promise of nanomedicine. First, the future of nanomedicine will depend on rational design of nanomaterials and tools based around a detailed and thorough understanding of biological and medical processes. For example, drug carrier design and targeting strategies may vary in relation to the type, developmental stage, and location of the disease. Second, more complex systems such as multifunctional nanop2010. Since 2010, she has been a post graduate in College of Chemistry & in Hebei University. She works under the guidance of Zhang. Her work includes the research about the effects of rare earth elements and rare earth nanop2011. During his doctoral training, he pursued projects focusing on basic research in cardiovascular diseases. [SEP] Justify:

Output: The text corroborates the claim by discussing the substantial developments in nanomedicine over the last ten years and emphasizes the importance of nanomaterials in various fields, including tissue engineering. It indicates that future advancements in nanomedicine will rely on the rational design of nanomaterials tailored for specific medical applications, suggesting a pathway towards more effective treatments, potentially including cancer therapies.


Input: Task: contrast the claim using the given text. Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: 17)Hall et al [42], 2019; abstinenceFacebook, Instagram, Snapchat, and Twitter4 groups: 1 week, 2 weeks, 3 weeks, and 4 weeksControl130; IG 1 week: 28, IG 2 weeks: 17, IG 3 weeks: 24, and IG 4 weeks: 26; CG: 3518-68 (26. 80, 11. 40)Hanley et al [43], 2019; AustraliaRCTFull abstinenceFacebook and Instagram1 weekControl78; IG: 40, CG: 3818-48 (30. 85, 7. 12)Lambert et al [44], 2022; abstinenceFacebook, Twitter, TikTok, and Instagram1 weekControl154; IG: 81, CG: 73≥18 (28. 90, 12. 75)Mitev et al [45], 2021; and BulgariaRCT (crossover trialf)Full abstinenceGeneral3 daysControl232; IG: 116, CG: 11618-71 (24. 70, N/Rg)Mosquera et al [46], 2020; abstinenceFacebook1 weekControl167; IG: 77, CG: 90N/R; undergraduatesPrzybylski et al [47], 2021; United Kingdom, United States, and Hong KongRCT (crossover trial)Full abstinenceGeneral1 dayControl297; IG: 297, CG: 29718-56 (20. 50, 2. 86)Tromholt [48], 2016; DenmarkRCTFull abstinenceFacebook1 weekControl888; IG: 516, CG: 372N/R (34. 00, 8. 74)Turel et al [49], 2018; United States2×2 RCTFull abstinenceFacebook1 weekControl555; IG: 413, CG: 14219-54 (24. 01, 4. 14)Vally and D’Souza [50], 2019; abstinenceGeneral1 weekControl78; IG: 39, CG: 3918-27 (22. 13, N/R)Vanman et al [51], 2018; AustraliaRCTFull abstinenceFacebook5 daysControl138; IG: 60, CG: 7818-40 (22. [SEP] Justify:

Output: The text contrasts the claim as it discusses various studies indicated by their abbreviations and control groups, likely examining the effects of abstaining from social media platforms like Facebook and Instagram. The mention of these studies implies that there is an investigation into the negative impacts or at least neutral effects of social media, rather than an assertion that social media algorithms have a positive impact on mental well-being.


Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: 20 43. 70 49. 17 62. 07 GEC-CNN + InSpelPOS 66. 23 51. 18 57. 74 72. 00 GEC-Trans + InSpelPOS 72. 09 64. 89 68. 30 74. 33 GEC-Trans + 65. 72 56. 33 60. 66 72. 82 GEC-Trans + Pattern-POS 68. 71 61. 19 64. 73 73. 43 DOI: 10. 7717/peerjcs. 2122/table-3 Notes: Numbers in bold refer to the largest values. Dynamic decoding We evaluate the performance of SiaGEC using dynamic decoding and explore Word embedding, and various BPE settings, including 30k and 1,000 WordPiece units. Figure 3 shows that the incorporation of GEC-Trans with dynamic decoding and word embedding achieved F1 score of 70. 93, marking an improvement of 2. 63 points. Dynamic decoding enhances the model’s capacity to comprehend and rectify errors within the broader sentence context, prioritizing critical errors while mitigating over-correction. We also investigated the impact of different BPE settings to address challenges related to unknown words. Initially, we adopted a 30k WordPiece unit configuration, consistent with previous work in Musyafa et al. (2022), resulting in performance gains of 71. 36 for the F1 score and 80. 71 for BLEU-4. Furthermore, we observed enhancements in the GEC-Trans + dynamic decoding model by employing a 1000 WordPiece unit BPE, raising the F1 score from 71. 36 to 72. 61 and the BLEU score from 80. 71 to 84. 43. Figure 3 presents the performance of SiaGEC with dynamic decoding under the 30k and 1k BPE settings. Figure 3: The performance of SiaGEC for automatic correction of Indonesian errors is equipped with dynamic decoding (DD) and BPE variations (30k and 1k). Download full-size image DOI: 10. 7717/peerjcs. 2122/fig-3 Multi-pass decoding In the realm of correcting text fraught with multiple grammatical errors, using a single-pass inference approach proves to be a formidable challenge due to the intricate nature of human language. Ge, Wei & Zhou (2018) pioneered a multi-round correction method to enhance the fluency of GEC systems. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the performance of the SiaGEC model in correcting text errors, the methods used in dynamic decoding, and BPE settings, without providing any information related to semantic memory or its involvement in understanding word meanings and sentence structures.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: Currently serving in College of Basic Medicine, Hebei University, he proceeds to study in vascular biology. His major academic work has been published in some leading scholarly journals such as Vasc Biol. Jinchao ZhangProf. Zhang obtained his PhD in Chemistry from (2001) and postdoctoral training in the (2001–2003) and of (2003–2006). He joined the in 2007. Now he is the professor of Hebei University, the PhD supervisor, the winner of for Scholars, the member of National Bio-inorganic Committee, the Director of of Hebei Province, and the Director of Center of Hebei University. Prof. Zhang has published over 80 peer-reviewed scientific papers and 12 patents/patent applications. Now Dr. Zhang’s group is developing novel nanomaterial for biological functions and applications. Xing-Jie LiangDr. Xing-got his PhD at Laboratory of Biomacromolecules, Institute of Biophysics at CAS. He finished his postdoc at Center for and worked as a at. Dr. Liang worked on Molecular imaging at School of Medicine, before he became deputy director of CAS for of Nanomaterials and Nanosafety, for Nanoscience and Technology of China. Dr. Liang is currently an editorial board member of “Sinica” and “Current Nanoscience” “Advances in Nano Research”. Developing drug delivery strategies for prevention/treatment of AIDS and cancers are current programs ongoing in Dr. Liang’s lab based on understanding of basic physio-chemical and biological processes of nanomedicine. This work was supported in part by project (No. 30970784, No. 81171455, No. 21271059, No. 20971034 and No. 81200078), Program of China (2009CB930200), a grant (31225009) from the of China, the State High-Plan (2012AA020804) and of Sciences (CAS) “Program” (07165111ZX), and for the of of China (No. 20111301110004). 1. Carbon nanotubes introduced into the abdominal cavity of mice show asbestos-like pathogenicity in a pilot study. 2008;3:423–8. 10. 1038/nnano. 2008. 111Search in 2. . [SEP] Justify:

Output: The text corroborates the claim as it mentions that Dr. Liang's lab is developing drug delivery strategies for the prevention and treatment of cancers, which indicates that nanomaterials are being utilized in the development of effective cancer treatments.


Input: Task: contrast the claim using the given text. Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: 43, N/R)Therapy-based interventionsChen et al [22], 2022; ChinaRCTGroup psychological counselingGeneral1 monthControl60; IG: 30, CG: 30N/R; undergraduatesHou et al [40], 2019; China2×2 RCTCognitive reconstruction, reminder cards, and diariesGeneral2 weeksControl38; IG: 21, CG: 17N/R (19. 71, 1. 43)O’Connell [35], 2020; EmiratesPre-post study1 hour per week mindfulness workshopGeneral5 weeksNone24; N/R18-25 (N/R)and Ahmadi [38], 2018; IranRCTReality therapy mobile app+reflective questionnairesGeneral2 weeksControl (only questionnaires)200; IG: 100, CG: 10018-28 (N/R)Throuvala et al [39], 2020; -based appGeneral10 daysControl143; IG: 72, CG: 7118-32 (20. 72, 3. 12)Zhou et al [37], 2021; -based part abstinence (4 of 7 weekdays)+daily reflective diariesGeneral2 weeksControl (social media as usual+daily diaries)65; IG: 33, CG: 32N/R (28. 80, 4. 90)Interventions involving limited social media useBrailovskaia et al [52], 2020; GermanyRCTLimited use (20 min/d)Facebook2 weeksControl286; IG: 140; CG: 14618-59 (25. 39, 5. 89)Graham et al [53], 2021; use (10 min/d)Facebook, Instagram, and Snapchat1 weekControl184; IG: 92, CG: 9218-61 (22. 46, 6. [SEP] Justify:

Output: The text references various studies and interventions related to social media use and mental health, specifically mentioning interventions that involve limited social media use. This implies that there are conditions under which social media can have a negative impact on user mental well-being, thus contradicting the claim that social media algorithms always have a positive impact.


Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: This method entails iteratively refining a sentence, addressing its errors in multiple rounds, thereby progressively enhancing its fluency. In our SiaGEC model, we have integrated this approach. Initially, we trained a new version of SiaGEC from Right to Left (SiaGEC R2L) which receives an input sentence and produces an initial correction in a single round. Instead of treating this initial correction as the final output, we feed it into the (SiaGEC L2R) model to further refine the sentence in a multi-round fashion. This dynamic process results in our ultimate prediction, thereby capturing a more comprehensive correction path. In our experimental evaluation, we have established two baseline scenarios. In the first baseline, we follow the order of correction by first utilizing SiaGEC L2R and subsequently applying SiaGEC R2L. In the second baseline, we reverse the correction order, employing SiaGEC R2L before SiaGEC L2R. The results, as demonstrated in Table 4, indicate increases of 2. 28 and 3. 24 points in recall and 0. 42 and 1. 2 points in F-score for both baselines. However, it is worth noting that the precision exhibits an average decrease of 0. 89 and 0. 23 points in both scenarios. This decline in precision may be attributed to a potential imbalance issue between the two correction models (Liu et al. , 2016). Table 4: SiaGEC model performance using multipass correction in two scenarios, numbers in bold refer to the largest values. Recall F1 score BLEU-4 SiaGEC L2R → SiaGEC R2L 81. 21 66. 34 73. 03 84. 13 SiaGEC R2L → SiaGEC L2R 82. 17 67. 00 73. 81 85. 33 DOI: 10. 7717/peerjcs. 2122/table-4 We evaluated the performance of the SiaGEC + multipass correction model by comparing it with recent Indonesian GEC systems. In this analysis, we considered several noteworthy systems. Lin et al. (2021) proposed an Indonesian GEC model that leveraged Part-of-Speech (POS) tags and was trained on a substantial dataset comprising 10,000 sentences, which successfully corrected 10 types of grammatical errors, achieving an F1 score of 55. 10. [SEP] Justify:

Output: The text does not address the claim regarding semantic memory and its role in understanding meanings of words and sentences. Instead, it focuses on the performance evaluation of the SiaGEC model for grammatical error correction, outlining methodologies and outcomes relevant to computational linguistics. Therefore, it is categorized as irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: Targeting and sensing cancer cells with ZnO nanoprobes in vitro. 2011;33:1891–6. 10. 1007/s10529-011-0641-5Search in 26. . Upconversion fluorescence imaging of cells and small animals using lanthanide doped nanocrystals. Biomaterials 2008;29:937–43. 10. 1016/j. biomaterials. 2007. 10. 051Search in 27. . One-Pot synthesis of carboxyl-functionalized rare earth fluoride nanocrystals with monodispersity, ultrasmall size and very bright luminescence. 2011;16:2158–63. 10. 1002/ejic. 201001149Search in 28. . Synthesis of colloidal upconverting monodisperse nanocrystals. 2007;7:847–52. 10. 1021/nl070235+Search in 29. Heer S, Kömpe K, Güdel H-U, Haase M. Highly efficient multicolour upconversion emission in transparent colloids of lanthanide-doped NaYF4 nanocrystals. 2004;17:2102–5. 10. 1002/adma. 200400772Search in 30. Yi G, Chow G. Core/shell/shell nanop3. 10. 1021/cm062447ySearch in 31. ’. Proton-sponge coated quantum dots for siRNA delivery and intracellular imaging. J Soc 2008;16:9006–12. 10. 1021/ja800086uSearch in 32. Qi L, Gao X. Quantum dot-amphipol nanocomplex time imaging of siRNA. ACS Nano 2008;2:1403–10. 10. 1021/nn800280rSearch in 33. . Targeted quantum dot conjugates for siRNA delivery. 2007;18:1391–6. 10. 1021/bc060367eSearch in 34. . In vivo molecular and cellular imaging with quantum dots. Biotechnol 2005;16:63–72. 10. 1016/j. copbio. 2004. 11. 003Search in 35. Alivisatos AP. Semiconductor clusters, nanocrystals, and quantum dots. [SEP] Justify:

Output: The text corroborates the claim by discussing various types of nanomaterials, such as ZnO nanoprobes and lanthanide-doped nanocrystals, that are utilized for targeting and imaging cancer cells. The mention of these advanced nanomaterials suggests their potential application in the development of more effective cancer treatments.


Input: Task: contrast the claim using the given text. Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: 83)Hunt et al [54], 2018; use (10 min/d)Facebook, Instagram, and Snapchat3 weeksControl143; N/RN/R; undergraduatesHunt et al [55], 2021; use (30 min/d)Facebook, Instagram, Twitter, and Snapchat3 weeks(1) Control and (2) limited active group (30 min/d+1 action every 3 min, eg, posting and replying)88; N/RN/R; undergraduatesThai et al [56], 2021; CanadaRCTLimited use (60 min/d)and Tumblr3 weeksControl38; IG: 16, CG: 2217-25 (N/R, 0. 94)aTargeting any social media platform. bRCT: randomized controlled trial. cUsual social media use. dIG: intervention group. eCG: control group. fAll participants receive all interventions, but the order in which they receive them (the sequence) is randomized. gN/R: not reported. hCBT: cognitive behavioral therapy. Sample CharacteristicsSample sizes ranged from 24 to 888 individuals, with 44% (10/23) of the studies including a sample size of <100 people. Where provided, sample ages ranged from 17 to 71 years, and 61% (14/23) of the studies reported mean ages between 20 and 30 years. Of the 23 studies, 4 (17%) did not provide ages and categorized participants as undergraduates [22,46,54,55]. A little more than half (12/23, 52%) of the studies recruited participants via university sampling, 30% (7/23) used web advertisements, and 17% (4/23) combined these methods [39,42,51,53]. Quality AssessmentNearly all studies (22/23, 96%) were given a weak global score, and no studies achieved a strong global score. Only the study by Throuvala et al [39] achieved a moderate score and this study showed a beneficial effect of the intervention on outcomes. Most of the studies were subject to selection bias, with 70% (16/23) being of moderate quality and 30% (7/23) being of weak quality on this criterion, because most of the studies (16/23, 70%) used convenience sampling from university populations. [SEP] Justify:

Output: The text contrasts the claim by discussing the outcomes of various studies concerning social media use. It mentions that nearly all studies (22/23) were assigned a weak global score for quality, indicating that their results may not reliably support positive impacts on mental well-being. Furthermore, it highlights issues such as selection bias and a lack of strong quality in the evidence presented, which implies that the effects of social media algorithms on mental well-being cannot be deemed universally positive.


Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: Additionally, Musyafa et al. (2022) introduced a Transformer-based GEC system tailored for Indonesian, augmented with advanced copying mechanisms, reported 71. 94 F1. Table 5, shows a comparison of precision, recall, F1, and BLEU scores, and clearly demonstrates that SiaGEC surpasses the performance of existing GEC systems. Table 5: Performance of SiaGEC as compared to the existing Indonesian GEC systems, numbers in bold refer to the largest values. Recall F1 score BLEU-4 Lin et al. (2021) 59. 40 42. 60 55. 10 N/A Musyafa et al. (2022) 71. 14 72. 76 71. 94 78. 13 SiaGEC 82. 17 67. 00 73. 81 85. 33 DOI: 10. 7717/peerjcs. 2122/table-5 Case study In this section, we evaluated how well the model performs using a case study with practical scenarios. The examples presented in this real-world scenario come from the Indonesian CC100 monolingual corpus. We showcased the output produced by various versions of SiaGEC, including the baseline Transformer-based model, the Transformer with dynamic decoding, and the Transformer with both dynamic and multi-pass decoding, as outlined in Table 6. Additionally, we provided the source, target, and English translation. The provided examples have several error categories as defined by Musyafa et al. (2022), such as spelling errors in 1, 2, 5, 6, and 7. The syntactic or grammatical errors are in 8, 9, and 11. The word order errors are in numbers 3, 4, and 10. The punctuation error is in number 8. At the outset, the baseline model corrected all spelling errors that are in numbers 1, 2, 5, 6, and 7, but failed to correct word choice errors, punctuation errors, and grammatical errors that are in numbers 3, 4, 8, 9, 10, and 11. Then the second baseline (Transformer + dynamic decoding) corrected all spelling errors, grammatical errors, and several word orders, which are in numbers 1, 2, 4, 5, 6, 7, 9, and 11. However, the second model failed to correct errors in punctuation and word order, numbers 3, 8, and 10. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the performance of a GEC system and the evaluation of models using specific case studies, without addressing the concept of semantic memory or its role in understanding meanings of words and sentences.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: Science 1996;271:933–6. 10. 1126/science. 271. 5251. 933Search in 36. . Photochemical instability of CdSe nanocrystals coated by hydrophilic thiols. J Soc 2001;123:8844–50. 10. 1021/ja016424qSearch in 37. Quantum rod bioconjugates as targeted probes for confocal and two-photon fluorescence imaging of cancer cells. Nanolett 2007;7:761–5. 10. 1021/nl063031mSearch in 38. . In vivo imaging of quantum dots encapsulated in phospholipid micelles. Science 2002;298:1759–62. 10. 1126/science. 1077194Search in 39. . Quantum dot-based theranostics. Nanoscale 2010;2:60–8. 10. 1039/B9NR00178FSearch in 40. . Development of multifunctional nanop51. 10. 2174/157016309787581066Search in 41. Enhanced intratumoral uptake of quantum dots concealed within hydrogel nanop5102. 10. 1088/0957-4484/19/48/485102Search in 42. . Folate-mediated tumor cell uptake of quantum dots entrapped in lipid nanop34. 10. 1016/j. jconrel. 2007. 08. 028Search in 43. Diagaradjane P, Orenstein-Cardona JM, Colón- Imaging epidermal growth factor receptor expression in vivo: pharmacokinetic and biodistribution characterization of a bioconjugated quantum dot nanoprobe. Res 2008;14:731–41. 10. 1158/1078-0432. CCR-07-1958Search in 44. Peptide-labeled near-infrared quantum dots for imaging tumor vasculature in living subjects. Nanolett 2006;6:669–76. 10. 1021/nl052405tSearch in 45. Functionalized near-infrared quantum dots for in vivo tumor vasculature imaging. Nanotechnology 2010;21:145105. 10. 1088/0957-4484/21/14/145105Search in 46. Bioconjugated quantum dots for multiplexed and quantitative immunohistochemistry. [SEP] Justify:

Output: The text corroborates the claim by mentioning various studies and advancements involving nanomaterials, specifically quantum dots and their applications in cancer cell imaging and therapy. For instance, it discusses 'quantum dot-based theranostics' and 'folate-mediated tumor cell uptake of quantum dots,' which indicate that nanomaterials are indeed being explored for cancer treatment applications.


Input: Task: contrast the claim using the given text. Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: Most of the studies (21/23, 91%) did not report blinding of the researcher or participants. A little more than a third (8/23, 35%) of the studies were weak in study design because although they randomized participants, they did not report how they did this. The studies had relatively low withdrawals and dropouts, with a little more than half (12/23, 52%) reporting that ≥80% of the participants completed the studies. Less than half (9/23, 39%) of the studies fully accounted for confounding variables. A little more than half (12/23, 52%) demonstrated that the data collection tools used were reliable and valid. Scores for all sections are provided in Multimedia 3. The main outcomes related to mental well-being reported in the studies were depression, life satisfaction, anxiety, fear of missing out (FOMO), mental well-being, positive affect, negative affect, loneliness, stress, self-esteem, and mindfulness. Depression was the most common outcome that was assessed (10/23, 44%), followed by life satisfaction (9/23, 39%), mental well-being (8/23, 35%), and anxiety (6/23, 26%). The least common outcomes that were assessed were self-esteem (3/23, 13%) and mindfulness (2/23, 9%). Most of the studies (18/23, 78%) investigated >1 mental well-being outcome. More than a third (9/23, 39%) of the studies demonstrated improvements in well-being–related outcomes. Almost one-third (7/23, 30%) of the studies found mixed effects across different well-being–related outcomes [35,41,46,49-51,54], and almost a third (7/23, 30%) found no effect [42,43,45,47,52,53,56]. An overview of the effectiveness of the interventions by outcome is shown in Figure 2. The most improved outcome was depression, with 70% (7/10) of the studies that measured this outcome showing a benefit of the intervention, with large or medium effect sizes being reported [22,38,44,46,48,54,55], whereas 30% (3/10) showed no effect of the intervention [35,52,56]. [SEP] Justify:

Output: The text contrasts the claim by indicating that the studies reviewed present mixed results regarding mental well-being related to social media algorithms. Specifically, it states that although some studies demonstrated improvements in well-being (39%), a significant portion found no effect (30%) and some showed mixed effects (30%). Thus, the evidence does not support the idea that social media algorithms always have a positive impact, as the outcomes varied widely, with many studies indicating negligible or no benefits.


Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: Finally, the last model (Transformer + dynamic and multi-pass decoding) is able to correct all spelling, word order, and grammar errors but fails to correct one punctuation error, namely the comma in number 8. The good performance of our proposed model showed that it is able to identify and correct errors in Indonesian text. Meanwhile, the failure of our SiaGEC model to correct punctuation errors is not a big problem in Indonesian writing. SiaGEC is still acceptable and more effective than the first baseline model in the given example. Therefore, the proposed SiaGEC model has significant improvements over models from previous work. Table 6: Output of our SiaGEC model in several versions, words in bold refer to incorrect words. Source Indonisya1(s) kepulauan terbesar d2(s) dunia, adalah rumah populasi bagi3(o) yang beragam dengan lebih dari 270 penduduk juta4(o) memiliki warisan budaya yang kya5(s) dan mayoritas muslin6(s) sambil juga memiliki pemandangan yang menajubkan7(s) termasuk,8(p)pantai tropis-tropis9(g)hujan hutan10(o)lebat yang11(g). Target Indonesia, kepulauan terbesar di dunia, adalah rumah bagi populasi yang beragam dengan lebih dari 270 juta penduduk, memiliki warisan budaya yang kaya dan mayoritas Muslim, sambil juga memiliki pemandangan yang menakjubkan, termasuk pantai-pantai tropis dan hutan hujan yang lebat. Translation Indonesia, the world’s largest archipelago, is home to a diverse population of over 270 million people, with a rich cultural heritage and a predominantly Muslim majority, while also boasting breathtaking landscapes, including tropical beaches and dense rainforests. Trans. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the performance of a model for correcting spelling and grammar errors in the Indonesian language, rather than addressing the role of semantic memory in understanding meanings of words and sentences. It does not mention anything related to semantic memory or its function.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: 2007;2:1152–65. 10. 1038/nprot. 2007. 107Search in 47. Yezhelyev MV, Al- In situ molecular profiling of breast cancer biomarkers with multicolor quantum dots. 2007;17:3146–51. 10. 1002/adma. 200701983Search in 48. High throughput quantification of protein expression of cancer antigens in tissue microarray using quantum dot nanocrystals. Nanolett 2006;6:2881–6. 10. 1021/nl062111nSearch in 49. ’ Imaging of multiple mRNA targets using quantum dot based in situ hybridization and spectral deconvolution in clinical biopsies. 2006;22:628–36. 10. 1016/j. bbrc. 2006. 07. 122Search in 50. ’connell Semiautomated multiplexed quantum dot-based in situ hybridization and spectral deconvolution. J 2007;9:20–9. 10. 2353/jmoldx. 2007. 060119Search in 51. Reimer P, Tombach B. Abdominal radiology review 204. 10. 1007/s003300050535Search in 52. Monoclonal antibody A7-superparamagnetic iron oxide as contrast agent of MR imaging of rectal carcinoma. Cancer 2005;93:131–6. 10. 1038/sj. bjc. 6602668Search in 53. MR imaging of the her2/neu and 9. 2. 27 tumor antigens using immunospecific contrast agents. Imaging 2004;22:843–50. 10. 1016/j. mri. 2004. 01. 050Search in 54. . UV-enhanced cytotoxicity of thiol-capped CdTe quantum dots in human pancreatic carcinoma cells. 2009;188:104–11. 10. 1016/j. toxlet. 2009. 03. 013Search in 55. In vivo MRI detection of gliomas by chlorotoxin-conjugated superparamagnetic nanoprobes. Small 2008;4:372–9. 10. 1002/smll. 200700784Search in 56. Distribution of the folate receptor GP38 in normal and malignant cell lines and tissues. 1992;52:3396–401. [SEP] Justify:

Output: The text provides various references to studies involving nanomaterials, specifically mentioning quantum dots and their application in cancer treatment and imaging, which supports the claim that nanomaterials are being developed for more effective cancer treatments.


Input: Task: contrast the claim using the given text. Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: Anxiety was the next most improved outcome, with 50% (3/6) of the studies that assessed this outcome showing significant improvement in anxiety, with medium and large effect sizes being reported [38,39,44]; however, 50% (3/6) reported no effect on anxiety [35,54,56]. FOMO also improved in 50% (2/4) of the studies assessing this outcome, with medium and small effect sizes being reported [36,39], whereas 50% (2/4) found no effect on FOMO [35,54]. Brown and Kuss [36] also explored the effect on FOMO based on gender and identified no significant differences between men and women after the intervention. Mental well-being improved in 38% (3/8) of the studies assessing this outcome, with small, medium, and large effect sizes being reported [36,40,44], whereas 63% (5/8) found no significant improvements in mental well-being [35,42,45,53,54]. Self-esteem improved in 33% (1/3) of the studies assessing this outcome, with a medium effect size being reported [40], but 67% (2/3) found no effect of the intervention on self-esteem [47,54]. The other outcomes showed mixed and some negative results. Loneliness was reduced in 40% (2/5) of the studies that measured this outcome [22,54], whereas 40% (2/5) found no effect [42,51]; however, 1 (20%) of these 5 studies also found that the intervention increased loneliness, with a medium effect size being reported [50]. Mindfulness improved in 1 (50%) of the 2 studies that measured this outcome, with a large effect size being reported [39], but it was found to reduce in another study (1/2, 50%), with a small effect size being reported [35]. Life satisfaction improved in a third (3/9, 33%) of the studies that measured this outcome, with small, medium, and large effect sizes being reported [37,38,48], whereas another third (3/9, 33%) of the studies showed no effect [43,46,52], and 22% (2/9) found full abstinence to be harmful, reducing life satisfaction, with medium effect sizes being reported [50,51]. [SEP] Justify:

Output: The text contrasts the claim by presenting findings from multiple studies that indicate mixed and predominantly negative effects of social media on mental well-being. Specifically, while some studies report improvements in anxiety, FOMO, and life satisfaction, a significant number also found no effect or even harmful outcomes, such as increased loneliness and reduced life satisfaction. For example, it mentions that 63% of the studies found no significant improvements in mental well-being, and some studies noted harmful impacts on factors like loneliness and life satisfaction.


Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: Indonesia, kepulauan terbesar di dunia, adalah rumah populasi bagi3(o) yang beragam dengan lebih dari 270 penduduk juta4(o) memiliki warisan budaya yang kaya dan mayoritas muslim, sambil juga memiliki pemandangan yang menakjubkan termasuk,8(p)pantai tropis-tropis9(g) dan hujan hutan10(o)lebat yang11(g). Trans. + Dynamic decoding Indonesia, Kepulauan terbesar di dunia, adalah rumah populasi bagi3(o) yang beragam dengan lebih dari 270 juta penduduk, memiliki warisan budaya yang kaya dan mayoritas Muslim, sambil juga memiliki pemandangan yang menakjubkan termasuk,8(p) pantai tropis dan hutan tropis10(o) yang lebat. Trans. + Dynamic decoding + Multi-pass decoding Indonesia, kepulauan terbesar di dunia, adalah rumah bagi populasi yang beragam dengan lebih dari 270 juta penduduk, memiliki warisan budaya yang kaya dan mayoritas Muslim, sambil juga memiliki pemandangan yang menakjubkan termasuk,8(p) pantai tropis dan hutan hujan yang lebat. DOI: 10. 7717/peerjcs. 2122/table-6 experiments have yielded promising results and insights, but it is important to acknowledge certain aspects where our findings may not fully capture the complexities of the low-resource GEC. The experiments of this study have been focused on specific configurations, because the performance of machine learning models can be sensitive to hyperparameter choices, further exploration of hyperparameter tuning and sensitivity analysis is warranted to identify optimal settings for various scenarios and datasets. Furthermore, SiaGEC has demonstrated effectiveness in Indonesian GEC, but its generalizability to other languages may vary. Different languages exhibit unique grammatical structures, error patterns, and linguistic challenges. [SEP] Justify:

Output: The text does not provide any information related to semantic memory or its role in understanding the meanings of words and sentences. Instead, it primarily discusses information about Indonesia, its population, culture, and the performance of machine learning models in the context of grammatical error correction (GEC) in Indonesian. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: Search in 57. . Differential regulation of folate receptor isoforms in normal and malignant tissues in vivo and in established cell lines. Cancer 1993;73:2432–43. Search in 58. Harisinghani MG, Weissleder R. Sensitive, noninvasive detection of lymph node metastases. PLoS Medicine 2004;1:e66. 10. 1371/journal. pmed. 0010066Search in 59. . Core-shell silica@chitosan nanop4. 10. 1016/j. carbpol. 2010. 03. 033Search in 60. Xie J, Jon S. Magnetic nanop4. 10. 7150/thno. 4051Search in 61. Nanobubbles from gas-generating polymeric nanop8. 10. 1002/anie. 200903841Search in 62. . Biological effects of nanomaterials and drugs measured by the small-animal SPECT/CT imaging system in vivo. Sin 2010;16:691–701. Search in 63. . A multimodal nanop5. Search in 64. . Dendrimer-based nanoprobe for dual modality magnetic resonance and fluorescence imaging. Nanolett 2006;6:1459–63. 10. 1021/nl060765qSearch in 65. . “Two is better than one” – probes for dual-modality molecular imaging. 2009;12:3511–24. Search in 66. Controlling assembly of paired gold clusters within apoferritin nanoreactor for in vivo kidney targeting and biomedical imaging. J Soc 2011;133:8617–24. 10. 1021/ja200746pSearch in 67. . Targeting of drugs and nanop68. 10. 1083/jcb. 200910104Search in 68. la Fuente JM, Grazú V, et al. Multifunctional nanocarriers for diagnostics, drug delivery and targeted treatment across blood-brain barrier: perspectives on tracking and neuroimaging. Toxicol 2010;7:3. 10. 1186/1743-8977-7-3Search in 69. Torchilin VP. Targeted pharmaceutical nanocarriers for cancer therapy and imaging. AAPS J 2007;9:E128–47. 10. 1208/aapsj0902015Search in 70. [SEP] Justify:

Output: The text corroborates the claim by listing several research studies and articles that suggest the development and application of nanomaterials for cancer therapy and imaging, such as 'targeted pharmaceutical nanocarriers for cancer therapy and imaging' indicated by Torchilin VP in 2007. This context supports the assertion that nanomaterials are indeed being explored for more effective cancer treatments.


Input: Task: contrast the claim using the given text. Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: Of these 9 studies, 1 (11%) found mixed effects because a significant improvement in life satisfaction was found for women, with a large effect size being reported, but not for men [41]. For stress, 1 (25%) of the 4 studies that measured this outcome found reductions in stress, with a medium effect size being reported [39], but half (2/4, 50%) of the studies showed no effect of the intervention on stress [50,51], whereas 25% (1/4) showed mixed effects because absolute stress reduced but the relative stress score compared with the score at baseline did not [49]. For negative affect, 1 (20%) of the 5 studies that measured this outcome found that negative affect increased after the intervention, with a small effect size being reported [50], but the other studies (4/5, 80%) showed no effect [41,43,47,51]. Positive affect also did not change after the intervention in most of the studies (4/5, 80%) [43,47,50,51]; however, 20% (1/5) found mixed results because positive affect improved for women, with a small effect size being reported, but not for men [41]. Table 3. Effectiveness of social media use interventions on mental well-being sorted by intervention type. Study, yearOutcomesMeasuresComparison measurementPostintervention-reported values (unless labeled)Effect size (Cohen d) and interpretationMain findingDirection of effectInterventions involving full abstinence from social mediaBrown and Kuss [36], 2020FOMOaMental well-beingdifference between before and after the intervention (SD)−3. 20 (5. 22)d4. 00 (5. 97)d0. 55 (Me)0. 47 (Sf)Significant improvements after the intervention↑gFioravanti et al [41], 2020Life satisfactionPositive affectNegative affectmean difference between IGj and CGk for women and menWomen2. 40l5. 45l−0. 30Men1. 900. 50−2. 25Women0. 81 (Lm)1. 09 (L)0. 04 (Xn)Men0. 36 (S)0. 07 (X)0. [SEP] Justify:

Output: The text contrasts the claim by presenting evidence from multiple studies that show mixed or negative effects of social media interventions on mental well-being. It states that some studies found no improvement or even an increase in negative affect for certain demographics, indicating that the impact of social media algorithms is not uniformly positive.


Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: Extending SiaGEC to encompass a broader range of languages and language families would provide a more comprehensive understanding of the model’s applicability. Moreover, the evaluations have primarily focused on the technical performance of the models. However, the long-term impact of language correction systems should also consider user experience, user feedback, and potential ethical implications. On the other hand, future research should focus on incorporating real-world data to assess model performance in practical contexts. This can help validate the effectiveness of SiaGEC under more diverse and complex conditions. Furthermore, extending the model’s capabilities to correct errors in multiple languages is an exciting avenue for future research. This involves accommodating variations in linguistic structures and error types across different languages. In addition, investigating the long-term impact, user experience, and ethical implications of language correction systems is crucial. This includes gathering user feedback and addressing any ethical concerns that may arise from automated correction. As well as a more in-depth analysis of specific error types and their correction can provide insights into areas where the model excels and where it requires improvement. 10. 7717/peerj-cs. 2122/supp-1 Information and authors declare there are no competing interests. conceived and designed the experiments, performed the experiments, analyzed the data, performed the computation work, prepared figures and/or tables, authored or reviewed drafts of the 0. 2. 0). Zenodo. work is supported by the of in Analysis and Application (No. 2022B1212010011). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. 2022. One country, 700+ languages: NLP challenges for underrepresented languages and dialects in Indonesia. In: Proceedings of the 60th annual meeting of the Association for (: long papers). Dublin, Ireland. Association for Computational Linguistics. 7226-7249. 2019. The BEA-2019 shared task on grammatical error correction. In: Proceedings of the fourteenth workshop on innovative use of NLP for building educational applications. Florence, Italy. Association for Computational Linguistics. 52-75. 2023. Rule based fuzzy computing approach on self-supervised sentiment polarity classification with word sense disambiguation in machine translation for hindi language. ACM Transactions on Asian and Low-22(5):153. 2019. [SEP] Justify:

Output: The text is irrelevant to the claim, as it discusses the broader implications of extending a language model and does not address semantic memory, its involvement in understanding meanings, or the specifics of word and sentence comprehension.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: Sumer B, Gao J. Theranostic nanomedicine for cancer. Nanomedicine 2008;3:137–40. 10. 2217/17435889. 3. 2. 137Search in 71. . Nanomaterials for cancer therapy and imaging. 2011;31:295–302. 10. 1007/s10059-011-0051-5Search in 72. . Advances in photodynamic therapy of cancer. 2011;7:234–47. 10. 2174/157339411796234889Search in 73. -P. Targeted therapy of cancer using photodynamic therapy in combination with multi-faceted anti-tumor modalities. Pharmaceuticals 2010;3:1507–29. 10. 3390/ph3051507Search in 74. . Cancer nanotechnology: application of nanotechnology in cancer therapy. Today 2010;15:842–50. 10. 1016/j. drudis. 2010. 08. 006Search in 75. émann E. State of the art in the delivery of photosensitizers for photodynamic therapy. J B 2002;66:89–106. 10. 1016/S1011-1344(01)00267-6Search in 76. Mai H, Zhang Y. Highly efficient multicolor up-conversion emissions and their mechanisms of monodisperse NaYF4: Yb, Er core and core/shell-structured nanocrystals. J C 2007;111:13721–9. 10. 1021/jp073920dSearch in 77. Auzel F. Upconversion and anti-Stokes processes with f and d ions in solids. 2009;104:139–73. 10. 1021/cr020357gSearch in 78. Detection of cell and tissue surface antigens using up-converting phosphors: a new reporter technology. 1999;267:30–6. 10. 1006/abio. 1998. 2965Search in 79. . Highly-sensitive multiplexed in vivo imaging using pegylated upconversion nanop32. 10. 1007/s12274-010-0036-2Search in 80. Laser scanning up-conversion luminescence microscopy for imaging cells labeled with rare-earth nanophosphors. [SEP] Justify:

Output: The text corroborates the claim by referencing various studies and articles associated with the use of nanomaterials in cancer therapy and imaging, including 'Cancer nanotechnology: application of nanotechnology in cancer therapy' and 'Theranostic nanomedicine for cancer.' These references indicate that nanomaterials are indeed being developed and applied in effective cancer treatments.


Input: Task: contrast the claim using the given text. Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: 31 (S)Significantly improved life satisfaction and positive affect for women but not for men in the IG compared with those in the CG↕oHall et al [42], 2019Mental well-beingLonelinessFour items from the SF-36pA short scale for measuring loneliness in large surveys [57]Mean (SD)CG4. 79 (1. 31)2. 57 (1. 17)IG4. 81 (1. 31)2. 57 (1. 24)0. 02 (X)0. 00 (X)No significant difference for the IG compared with the CG across all measures↔qHanley et al [43], 2019Life satisfactionPositive affectNegative affectQuality of -18coefficients from multiple regression0. 05−0. 160. 100. 01 (X)0. 32 (S)0. 20 (S)No significant difference for the IG compared with the CG across all measures↔Lambert et al [44], 2022Mental well-beingdepression scaleGAD-7rMean (SD)CG45. 05 (8. 06)6. 95 (4. 45)5. 94 (4. 30)IG55. 93 (7. 65)d4. 84 (3. 89)d3. 88 (3. 84)l1. 38 (L)0. 50 (M)0. 51 (M)Significant improvements for the IG compared with the CG across all measures↑Mitev et al [45], 2021Mental well-beingDaily satisfaction question, self-esteem scale, and positive and negative affect scales were combined to create an overall composite score of participants’ well-beingF value and partial eta–squared valueF2,416=0. 11; P=. 89; ηp2=. 0010. 06 (X)No significant difference for the IG compared with the CG↔Mosquera et al [46], 2020Life satisfactionDepressionOne question taken from the question taken from the difference between before and after the intervention (SD)(3. 36)−0. 57 (2. [SEP] Justify:

Output: The text contrasts the claim by providing evidence that some studies found no significant difference in various measures of mental well-being between the intervention group (IG) and the control group (CG). For example, it mentions that 'No significant difference for the IG compared with the CG across all measures' for life satisfaction and mental well-being in some instances. This suggests that not all algorithms used in social media lead to positive impacts, which directly challenges the notion that these algorithms always have a beneficial effect.


Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: A neural grammatical error correction system built on better pre-training and sequential transfer learning. In: Proceedings of the fourteenth workshop on innovative use of NLP for building educational applications. Florence, Italy. Association for Computational Linguistics. 213-227 án. 2020. Unsupervised cross-lingual representation learning at scale. In: Proceedings of the 58th annual meeting of the association for computational linguistics. Association for Online. 8440-8451 Dahlmeier D, Ng HT. 2012. Better evaluation for grammatical error correction. In: Proceedings of the 2012 conference of the north american 2023. Statistical machine translation for indic languages. preprint Devlin J, Chang M-W, Lee K, Toutanova K. 2019. BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 conference of the 2014. Grammatical error correction using hybrid systems and type filtering. In: Proceedings of the eighteenth conference on computational natural language learning: shared task. Baltimore, Maryland. Association for Computational Linguistics. 15-24. 2018. Fluency boost learning and inference for neural grammatical error correction. In: Proceedings of the 56th annual meeting of the association for computational linguistics (: long papers). Melbourne, Australia. Association for Computational Linguistics. 1055-1065 Ghosh I. 2020. Ranked: The 100 most spoken languages around the world. Visual Capitalist. Grundkiewicz R, Junczys-Dowmunt M, Heafield K. 2019. Neural grammatical error correction systems with unsupervised pre-training on synthetic data. In: Proceedings of the fourteenth workshop on innovative use of NLP for building educational applications. Florence, Italy. Association for Computational Linguistics. 252-263. 2019. LinearFold: linear-time approximate RNA folding by 5’-to-3’dynamic programming and beam search. Bioinformatics 35(14):i295-i304. 2018. Wronging a right: generating better errors to improve grammatical error detection. In: Proceedings of the 2018 conference on empirical methods in natural language processing. Brussels, Belgium. Association for Computational Linguistics. 4977-4983 Kingma DP, Ba J. 2015. [SEP] Justify:

Output: The text is irrelevant to the claim as it predominantly discusses various proceedings and papers related to grammatical error correction and natural language processing without addressing the concept of semantic memory or its role in understanding meanings of words and sentences.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: 2009;81:930–5. 10. 1021/ac802072dSearch in 81. Non-blinking and photostable upconverted luminescence from single lanthanide-doped nanocrystals. 2009;106:10917–21. 10. 1073/pnas. 0904792106Search in 82. . Near-infrared light induced in vivo photodynamic therapy of cancer based on upconversion nanop54. 10. 1016/j. biomaterials. 2011. 05. 007Search in 83. -L, Guillemin F, Barberi-Heyob M. Nanop21. 10. 1016/j. tibtech. 2008. 07. 007Search in 84. . Photodynamic activity of hematoporphyrin conjugates with gold nanop7. Search in 85. Ma J, Chen J-Y, Idowu M, Nyokong T. Generation of singlet oxygen via the composites of water-soluble thiol-capped CdTe quantum dots-sulfonated aluminum phthalocyanines. J B 2008;112:4465–9. 10. 1021/jp711537jSearch in 86. . Semiconductor quantum dots for photodynamic therapy. J Soc 2003;125:15736–7. 10. 1021/ja0386905Search in 87. . Nanop37. 10. 1016/j. addr. 2008. 08. 003Search in 88. . Photo-thermal tumor ablation in mice using near infrared-absorbing nanop6. 10. 1016/j. canlet. 2004. 02. 004Search in 89. Liao X, Zhang X. Preparation, characterization and cytotoxicity of carbon nanotube-chitosan-phycocyanin complex. Nanotechnology 2012;23:035101. 10. 1088/0957-4484/23/3/035101Search in 90. . Cancer photothermal therapy in the near-infrared region by using single-walled carbon nanotubes. J 2009;14:021009. 10. 1117/1. 3078803Search in 91. Carbon nanotube-enhanced thermal destruction of cancer cells in a noninvasive radiofrequency field. Cancer 2007;110:2654–65. 10. [SEP] Justify:

Output: The text corroborates the claim by mentioning various studies and applications of nanomaterials, such as 'photodynamic therapy of cancer based on upconversion nanoparticles' and 'cancer photothermal therapy in the near-infrared region by using single-walled carbon nanotubes.' These examples illustrate the ongoing development and use of nanomaterials in creating more effective cancer treatments.


Input: Task: contrast the claim using the given text. Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: 97)l—tSignificant improvements for the IG compared with the CG for depression but not for life satisfaction↕Przybylski et al [47], 2021Positive affectNegative affectSelf-esteem-(10-item version)Mean (SD)CG2. 78 (0. 78)u1. 71 (0. 69)3. 01 (0. 49)IG2. 72 (0. 81)1. 81 (0. 71)2. 99 (0. 50)0. 08 (X)0. 14 (X)0. 04 (X)No significant difference for the IG compared with the CG↔Tromholt [48], 2016Life satisfactionDepression or emotionLife satisfaction questionnaire developed for the investigationFour items from the CES-Dv and 4 items from PANAS combinedMean (SD)CG7. 74 (1. 43)33. 99 (6. 81)IG8. 11 (1. 23)d36. 21 (6. 09)d0. 37 (S)1. 22 (L)Significant improvements for the IG compared with the CG across all measures↑Turel et al [49], 2018Absolute stressRelative stressmeans (95% CI)CG0. 50 (0. 33 to 0. 68)0. 09 (0. 04 to 0. 15)IG0. 72 (0. 62 to 0. 82)l0. 14 (0. 10 to 0. 17)0. 18 (X)0. 13 (X)Significantly reduced absolute stress in the IG but not relative stress compared with the CG↕Vally and D’Souza [50], 2019Life satisfactionPositive affectNegative affectand Scale for AdultsPSSMean (SD)CG5. 16 (1. 14)3. 31 (0. 81)2. 36 (0. 84)3. 08 (1. 13)1. 78 (0. 51)IG4. 37 (1. 26)l3. 34 (0. 63)2. 60 (0. 89)l3. 81 (1. 30)l1. 79 (0. 49)0. 66 (M)0. 04 (X)0. 28 (S)0. 60 (M)0. [SEP] Justify:

Output: The text contrasts the claim by presenting mixed findings regarding the effects of social media on mental well-being. It notes significant improvements in depression among the intervention group (IG) compared with the control group (CG), but these improvements do not extend to life satisfaction, suggesting that the overall impact of social media algorithms is not uniformly positive for all aspects of mental health.


Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: A method for stochastic optimization. In: International conference on learning representations (ICLR),vol. 5. San Diego, California. 6. 2020. Liputan6: a large-scale indonesian dataset for text summarization. In: Proceedings of the 1st conference of the asia-pacific 2016. Overview of NLP-TEA 2016 shared task for chinese grammatical error diagnosis. In: Proceedings of the 3rd workshop on natural language processing techniques for educational applications (2016). Osaka, Japan. 2016 Organizing Committee. 40-48. 2022. Residual learning of neural text generation with n-gram language model. In: Findings of the Association for Computational Linguistics: EMNLP 2022. Abu Dhabi, Emirates. Association for Computational Linguistics. 1523-1533. 2019. Corpora generation for grammatical error correction. In: Proceedings of the 2019 conference of the 2021. A framework for indonesian grammar error correction. ACM Transactions on Asian and Low-20(4):57. 2023. A BERT-based unsupervised grammatical error correction framework. preprint. 2016. Agreement on target-bidirectional neural machine translation. In: Proceedings of the 2016 conference of the north american 2023. Semi-supervised learning and bidirectional decoding for effective grammar correction in low-resource scenarios. PeerJ 9:e1639 Meyer F, Buys J. 2023. Subword segmental machine translation: unifying segmentation and target sentence generation. In: Findings of the Association for Computational Linguistics: ACL 2023. Toronto, Canada. Association for Computational Linguistics. 2795-2809. 2014. The first QALB shared task on automatic text correction for arabic. In: Proceedings of the EMNLP 2014 workshop on arabic natural language processing (ANLP). Doha, Qatar. Association for Computational Linguistics. 39-47. 2022. Automatic correction of indonesian grammatical errors based on transformer. 12(20):10380 Náplava J, Straka M. 2019. Grammatical error correction in low-resource scenarios. In: Proceedings of the 5th workshop on noisy user-generated text (W-NUT 2019). Hong Kong, China. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses various academic conference proceedings and topics related to natural language processing and machine translation without addressing semantic memory or its role in understanding meanings of words and sentences.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: 1002/cncr. 23155Search in 92. Thermal ablation of tumor cells with carbon nanotubes. 2008;105:8697–702. 10. 1073/pnas. 0803557105Search in 93. PEG branched polymer for functionalization of nanomaterials with ultralong blood circulation. J Soc 2009;131:4783–7. 10. 1021/ja809086qSearch in 94. ’Agostino R, Olson J, et al. Increased heating efficiency and selective thermal ablation of malignant tissue with DNA-encased multiwalled carbon nanotubes. ACS Nano 2009;3:2667–73. 10. 1021/nn900368bSearch in 95. . In vivo near-infrared mediated tumor destruction by photothermal effect of. ACS Nano 2009;3:3707–13. 10. 1021/nn900904hSearch in 96. -T, Liu Z. Optimization of surface chemistry on single-walled carbon nanotubes for in vivo photothermal ablation of tumors. Biomaterials 2011;32:144–51. 10. 1016/j. biomaterials. 2010. 08. 096Search in 97. Kam NW, O’. Carbon nanotubes as multifunctional biological transporters and near-infrared agents for selective cancer cell destruction. 2005;102:11600–5. 10. 1073/pnas. 0502680102Search in 98. . Multiplexed multicolor Raman imaging of live cells with isotopically modified single walled carbon nanotubes. J Soc 2008;130:13540–1. 10. 1021/ja806242tSearch in 99. . Selective probing and imaging of cells with single walled carbon nanotubes as near-infrared fluorescent molecules. Nanolett 2008;8:586–90. 10. 1021/nl072949qSearch in 100. -T, Liu Z. Graphene in mice: ultrahigh in vivo tumor uptake and efficient photothermal therapy. Nanolett 2010;10:3318–23. 10. 1021/nl100996uSearch in 101. . Gold nanorods: electrochemical synthesis and optical properties. J B 1997;101:6661–4. 10. [SEP] Justify:

Output: The text supports the claim by discussing various studies and applications of nanomaterials, such as carbon nanotubes, for cancer treatment. For instance, it mentions 'selective thermal ablation of malignant tissue with DNA-encased multiwalled carbon nanotubes' and 'in vivo near-infrared mediated tumor destruction by photothermal effect,' indicating that nanomaterials are indeed being developed and researched for enhancing cancer therapies.


Input: Task: contrast the claim using the given text. Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: 02 (X)Significantly reduced life satisfaction and increased negative feelings and loneliness for the IG compared with the CG but no difference in positive affect or stress↕Vanman et al [51], 2018Life satisfactionStressPositive affectNegative affectform of the Social and Scale for AdultsMean difference between before and after the intervention (SD)CG1. 85 (4. 97)Means not reported for other outcomesIG−0. 93l (5. 61)Means not reported for other outcomes0. 54 (M)The IG had significantly reduced life satisfaction compared with the CG but no other outcomes were significantly different↕Therapy-based interventionsChen et al [22], 2022DepressionLonelinessCES-D-20xULS-8yMean (SD)CG15. 70 (9. 73)17. 07 (3. 52)IG3. 00 (4. 65)d13. 17 (3. 04)d1. 67 (L)1. 19 (L)Significant improvements for the IG compared with the CG across all measures↑Hou et al [40], 2019Self-esteemMental health and well-beingChinese version of the Self-Esteem ScaleQuestionnaire developed from GHQ-30zMean (SD)CG28. 35 (3. 81)12. 35 (4. 58)IG30. 67 (3. 17)d15. 71(3. 89)l0. 66 (M)0. 79 (M)Significant improvements for the IG compared with the CG across all measures↑O’Connell [35], 2020well-being-DZung Self-ScaleMean difference between before and after the intervention (N/Rac)−0. 32l−0. 046−0. 0520. 360. 950. 32 (S)0. 05 (X)0. 07 (X)0. 03 (X)0. 12 (X)Significant reduction in mindfulness after the intervention but no difference in FOMO, well-being, depression, or anxiety↕and Ahmadi [38], 2018DepressionAnxietyLife satisfactionrankae (N/R)CG50. 9648. 7445. 56IG42. 30d43. 71d54. 72d0. 84 (L)0. 97 (L)1. [SEP] Justify:

Output: The text contrasts the claim by presenting findings that indicate social media can lead to significantly reduced life satisfaction and increased feelings of negativity and loneliness. It specifically mentions that the intervention group (IG) experienced decreased life satisfaction compared to the control group (CG), which suggests negative impacts contrary to the claim that social media algorithms always positively affect mental well-being.


Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: Association for Computational Linguistics. 346-356. 2014. The CoNLL-2014 shared task on grammatical error correction. In: Proceedings of the eighteenth conference on computational natural language learning: shared task. Baltimore, Maryland. Association for Computational Linguistics. 1-14 ’hAlalim A, Alsayed A. 2021. Bert multilingual and capsule network for arabic sentiment analysis. In: 2020 international conference on computer, control, electrical, and electronics engineering (). Piscataway. IEEE. 1-6. 2023. A low-resource approach to the grammatical error correction of Ukrainian. In: Proceedings of the second Workshop (UNLP). Dubrovnik, Croatia. Association for Computational Linguistics. 114-120 -J. 2002. Bleu: a method for automatic evaluation of machine translation. In: Proceedings of the 40th annual meeting of the association for computational linguistics. Philadelphia, Pennsylvania, USA. Association for Computational Linguistics. 311-318. 2021. A simple recipe for multilingual grammatical error correction. In: Proceedings of the 59th annual meeting of the association for computational linguistics and the 11th international joint conference on natural language processing (: short papers). Association for Computational Linguistics, Online. 702-707. 2016. Sentence-level grammatical error identification as sequence-to-sequence correction. In: Proceedings of the 11th workshop on innovative use of NLP for building educational applications. San Diego, CA. Association for Computational Linguistics. 242-251. 2016a. Improving neural machine translation models with monolingual data. In: Proceedings of the 54th annual meeting of the association for computational linguistics (: long papers). Berlin, Germany. Association for Computational Linguistics. 86-96. 2016b. Neural machine translation of rare words with subword units. In: Proceedings of the 54th annual meeting of the association for computational linguistics (: long papers). Berlin, Germany. Association for Computational Linguistics. 1715-1725. 2019. Proposed model for arabic grammar error correction based on convolutional neural network. In: 2019 international conference on computer, control, electrical, and electronics engineering (). Piscataway. IEEE. 1-6. 2022. [SEP] Justify:

Output: The text is primarily a list of references and does not directly address the claim regarding semantic memory and its role in understanding meanings. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: 1021/jp971656qSearch in 102. Nanoshell-mediated near-infrared thermal therapy of tumors under magnetic resonance guidance. 2003;100:13549–54. 10. 1073/pnas. 2232479100Search in 103. -Sayed IH, El-Sayed MA. Gold nanop93. 10. 2217/17435889. 2. 5. 681Search in 104. Anisotropic metal nanop70. 10. 1021/jp0516846Search in 105. Nikoobakht B, El-Sayed M. Preparation and growth mechanism of gold nanorods (NRs) using seed-mediated growth method. 2003;15:1957–62. 10. 1021/cm020732lSearch in 106. . Nanoengineering of optical resonances. Lett 1998;288:243–7. 10. 1016/S0009-2614(98)00277-2Search in 107. . Template-engaged replacement reaction: a one-step approach to the large-scale synthesis of metal nanostructures with hollow interiors. 2002;2:481–5. 10. 1021/nl025531vSearch in 108. Huang X, El-Sayed M. Gold nanop28. 10. 1016/j. jare. 2010. 02. 002Search in 109. . On the physical rationale of laser induced hyperthermia. Sci 1990;5:121–8. 10. 1007/BF02031373Search in 110. . Immunotargeted nanoshells for integrated cancer imaging and therapy. 2005;5:709–11. 10. 1021/nl050127sSearch in 111. Huang X, El--Sayed M. Cancer cell imaging and photothermal therapy in the near-infrared region by using gold nanorods. J Soc 2006;128:2115–20. 10. 1021/ja057254aSearch in 112. Verma A, Stellacci F. Effect of surface properties on nanop21. 10. 1002/smll. 200901158Search in 113. Surface chemistry-mediated penetration and gold nanorod thermotherapy in multicellular tumor spheroids. Nanoscale 2013;5:143–6. 10. [SEP] Justify:

Output: The text corroborates the claim by referring to various studies and applications involving nanomaterials, such as 'immunotargeted nanoshells for integrated cancer imaging and therapy' and 'gold nanorods' used in 'cancer cell imaging and photothermal therapy'. These examples illustrate that nanomaterials are indeed being applied in ways that enhance cancer treatment effectiveness.


Input: Task: contrast the claim using the given text. Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: 04 (L)Significant improvements within the IG across all measures↑Throuvala et al [39], 2020-7FoMOsMean (SD)CG3. 37 (0. 76)27. 94 (5. 24)17. 44 (4. 42)3. 32 (1. 22)IG3. 97 (0. 69)d24. 10 (4. 63)d14. 75 (4. 43)d2. 86 (1. 16)d0. 82 (L)0. 77 (M)0. 60 (M)0. 39 (S)Significant improvements for the IG compared with the CG across all measures↑Zhou et al [37], 2021Life satisfactionSWLSMean (SD)CG4. 37 (1. 06)IG4. 90 (1. 04)l0. 50 (M)Significant improvements for the IG compared with the CG↑Interventions involving limited social media useBrailovskaia et al [52], 2020Life satisfaction-21afMean difference (95% CI) between the groups−0. 57 (−1. 95 to 0. 81)0. 15 (−0. 90 to 1. 20)0. 10 (X)0. 03 (X)No significant improvement in the IG compared with the CG across both measures↔Graham et al [53], 2021Well-being(SD)CG3. 43 (0. 72)IG3. 51 (0. 64)0. 01 (X)No significant improvement in the IG compared with the CG↔Hunt et al [54], 2018depressionLow depressionSelf-esteemMental well-being-8-/RN/RN/R22. 834. 67N/RN/RIGN/RN/RlN/R14. 50l4. 10lN/RN/R—Significant improvements in depression and loneliness for the IG compared with the CG; no significance for other outcomes↕Hunt et al [55], 2021DepressionBDIMean (SD)CG28. 63 (5. 04)AGag16. 29 (5. 22)IG14. 80 (5. [SEP] Justify:

Output: The text contrasts the claim by discussing various studies that report mixed results regarding social media use on mental well-being. For instance, it mentions that some interventions involving limited social media use showed no significant improvement in life satisfaction and well-being measures in the intervention group (IG) compared with the control group (CG). This indicates that social media algorithms do not always have a positive impact on mental well-being, contradicting the claim that they always do.


Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: A response to any given word was considered to be “correct” if at least one property was correctly recalled. The numbers of paragraphs for which a “correct” response was given ranged (across participants) from 3 to 26 of the 36 paragraphs (mean = 17. 23, SD = 7. 27). A set of 2 × 2 repeated measures ANOVAs were conducted on the participant and item means, with the factor of Relatedness (related or unrelated) measured within subjects/items and Version measured between subjects/items. The proportion of correct responses was significantly higher for related than for unrelated paragraphs [Table 3; F 1(1, 20) = 172. 4, p <. 001; F 2(1, 34) = 152. 8 p <. 001]. Because of the large proportion of unrelated trials on which no information was correctly recalled (74 %), it was not possible to assess whether (for those items that were correctly recalled) more information was recalled for related than for unrelated paragraphs. Table 3 Cued-recall results: Performance for the related and unrelated words (calculated across participants)Full size table To assess whether memory performance was related to participants’ ratings of novelty, plausibility, and clarity, and to assess whether the effect of Relatedness was still significant when these variables were taken into account, an was conducted using the item means, with the factors of both Relatedness and Version measured between items and the factors of Novelty, Plausibility, and Clarity included as covariates. Because each word–paragraph combination had an individual rating on each of these measures, it was necessary to use a between-items approach to the analysis. As with the main analysis, we found a significant effect of Relatedness on the proportions of correct responses [F(1, 65) = 23. 1, p <. 001]. The covariates of Novelty, Plausibility, and Clarity were nonsignificant (p >. 2)Intrusion errors (i. e. , recall of incorrect information) were relatively rare (n = 90, 11. 4 % of the total responses). We found significantly more errors for unrelated words (n = 60, 63. 7%) than for related words (n = 30) on a binomial test (p =. 015). These errors consisted of three types. [SEP] Justify:

Output: The text does not directly address the claim regarding semantic memory and its involvement in understanding the meanings of words and sentences. Instead, it discusses experimental results related to the recall of words and the effects of relatedness on memory performance, which are tangential to the claim. Thus, it is deemed irrelevant.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: Ultrasonics sonochemistry detection and analysis of reactive oxygen species (ROS) generated by nano-sized TiO2 powder under ultrasonic irradiation and application in sonocatalytic degradation of organic dyes. 2011;18:177–83. 10. 1016/j. ultsonch. 2010. 05. 002Search in 127. Ultrasound activation of TiO2 in melanoma tumors. J 2011;149:190–5. 10. 1016/j. jconrel. 2010. 10. 012Search in 128. Baust JG, Gage A. The molecular basis of cryosurgery. BJU Int 2005;95:1187–91. 10. 1111/j. 1464-410X. 2005. 05502. xSearch in 129. Rubinsky B, Onik G. Cryosurgery: advances in the application of low temperatures to medicine. Refrig 1991;14:190–9. 10. 1016/0140-7007(91)90003-YSearch in 130. Rubinsky B. Cryosurgery. 2000;2:157–87. 10. 1146/annurev. bioeng. 2. 1. 157Search in 131. Salvage cryotherapy for recurrent prostate cancer after radiotherapy: variables affecting patient outcome. J 2002;20:2664–71. 10. 1200/JCO. 2002. 06. 086Search in 132. . Liver resection or cryotherapy for colorectal liver metastases a prospective case control study. 2005;20:507–20. 10. 1007/s00384-004-0723-0Search in 133. Yan JF, Liu J. Nanocryosurgery and its mechanisms for enhancing freezing efficiency of tumor tissues. Nanomedicine 2008;4:79–87. 10. 1016/j. nano. 2007. 11. 002Search in 134. . A new nano-cryosurgical modality for tumor treatment using biodegradable MgO nanop41. 10. 1016/j. nano. 2012. 02. 010Search in 135. Multihydroxylated [Gd@C82(OH)22]n nanop7. 10. 1021/nl051624bSearch in 136. [SEP] Justify:

Output: The text corroborates the claim by discussing various applications of nanomaterials, specifically mentioning 'nano-sized TiO2 powder' utilized in ultrasound activation within 'melanoma tumors.' Furthermore, it references 'nanocryosurgery' as a modality for tumor treatment, highlighting the engagement of nanomaterials in enhancing treatment efficacy for cancer patients.


Input: Task: contrast the claim using the given text. Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: 41)l—Significant improvements for IG participants who were highly depressed compared with CG and AG participants↑Thai et al [56], 2021AnxietyDepressionGAD-7Revised CES-DMean (SD)CGN/RN/RIG8. 54 (4. 27)N/R0. 62 (M)0. 57 (M)No significant improvement in the IG compared with the CG across both measures↔aFOMO: fear of missing out. bFoMOs: Fear of Scale. c: Warwick-Well-Being Scale. dP<. 001. eM: medium. fS: small. gBeneficial effect. hSWLS: Life Scale. iPANAS: Positive and Schedule. jIG: intervention group. kCG: control group. lP<. 05. mL: Large. nX: negligible. oMixed effects. pSF-36: 36-item Health Survey. qNo effect. rGAD-7: Disorder-7. sOECD: Organisation for Economic Co-operation and Development. tNot available (number in each group was not specified to calculate effect size). uAverage mean and SD reported across the 3 countries because the relationship among variables was the same across the countries. Estimates based on unadjusted means because the adjusted means were not provided. vCES-D: Center for Depression Scale. wPSS: Scale. xCES-D-20: Center for Depression Scale, 20-item version. yULS-8: University of Scale. zGHQ-30: Questionnaire-30. aaMAAS: Awareness Scale. abPWB: Psychological Well-Being Scale. acN/R: not reported. adBDI: Inventory. aeComparing the IG between before the intervention and after. The effect of the intervention between the IG and the CG was not reported and could not be calculated. afDASS-21: 21. agAG: active group (limited use of social media at 30 minutes per day plus 1 action every 3 minutes, eg, posting and replying). Figure 2. Summary of social media use intervention effects on mental well-being–related outcomes. FOMO: fear of missing out. Effectiveness by Intervention TypeFigure 3 shows an overview of the effectiveness of social media use interventions by intervention type. [SEP] Justify:

Output: The text contrasts the claim by presenting findings from an intervention study that did not demonstrate overall positive effects of social media usage on mental well-being. It mentions 'No significant improvement in the IG compared with the CG across both measures,' suggesting that the impact of social media may not be universally positive, challenging the assertion that social media algorithms always enhance mental well-being.


Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: Lexical decisionOne of the 15 participants was removed due to highly variable performance across different blocks and to a high proportion of very slow responses (SD = 342 ms, 28 % of responses greater than 1,000 ms). The remaining participants made between 0. 9 % and 15. 7 % errors, with response times that ranged between 475 and 878 ms. One of the trained words (“snow”) was inadvertently omitted from the experiment. Also, one of the untrained words (“sled”) was removed because its error rate was greater than 50 %. Only correct response times were included in the analyses. Individual responses that were greater than three standard deviations above the mean for that participant or shorter than 250 ms were excluded (1. 7 % of the responses to experimental items). Analyses were conducted on response times and error rates using means that were calculated across both participants and items (Fig. 1). Fig. 1Lexical decision results (Exps. 2 and 3): a Mean response times and b mean percentage errors for the subjects analyses. Error bars show standard errors adjusted to remove between-subjects varianceFull size image The first set of ANOVAs compared the response times and error rates for the trained words (combined across levels of Relatedness) with the untrained words. Condition (trained vs. untrained) was included as a within-subjects/-items variable for the subjects and items analyses, respectively. Version was included as a between-subjects variable for the subjects analysis and as a within-items variable for the items analysis. Participants responded significantly more slowly to the untrained words than to the trained words [F 1(1, 12) = 10. 3, p <. 01; F 2(1, 104) = 10. 7, p <. 001]. The participants also made marginally more errors to the untrained words than to the trained words [F 1(1, 12) = 3. 6, p =. 08; F 2(1, 104) = 3. 1, p =. 08]. The second set of analyses excluded the untrained words and compared the two types of trained words. Relatedness (related vs. unrelated) was included as a within-subjects/-items factor, and Version was included as a between-subjects/-items factor. There was no effect of Relatedness on response times [F 1(1, 12) = 0. [SEP] Justify:

Output: The text is primarily focused on the methodology and results of a lexical decision experiment, discussing participant performance and statistical analyses. It does not directly address semantic memory or its role in understanding meanings of words and sentences, thus it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: Potent angiogenesis inhibition by the particulate form of fullerene derivatives. ACS Nano 2010;4:2773–83. 10. 1021/nn100448zSearch in 137. Epigenetic modulation of human breast cancer by metallofullerenol nanop9. 10. 1039/c1nr10898kSearch in 138. . Metallofullerol nanop13. 10. 2217/nnm. 12. 95Search in 139. The scavenging of reactive oxygen species and the potential for cell protection by functionalized fullerene materials. Biomaterials 2009;30:611–21. 10. 1016/j. biomaterials. 2008. 09. 061Search in 140. Metallofullerene nanop54. 10. 1073/pnas. 0909707107Search in 141. . Drug delivery and nanop49. 10. 2147/IJN. S596Search in 142. . Nanotechnology-based drug delivery systems. J Toxicol 2007;2:16. 10. 1186/1745-6673-2-16Search in 143. Sledge G, Miller K. Exploiting the hallmarks of cancer: the future conquest of breast cancer. Cancer 2003;39:1668–75. 10. 1016/S0959-8049(03)00273-9Search in 144. . Poly(ethylene glycol)-modified nanocarriers for tumor-targeted and intracellular delivery. 2007;24:1405–14. 10. 1007/s11095-007-9284-6Search in 145. Barreto JA, O’. Nanomaterials: applications in cancer imaging and therapy. 2011;23:H18–40. 10. 1002/adma. 201100140Search in 146. Abdollahi A, Folkman J. Evading tumor evasion: current concepts and perspectives of anti-angiogenic cancer therapy. Updat 2010;13:16–28. 10. 1016/j. drup. 2009. 12. 001Search in 147. Increased antitumor activity, intratumor paclitaxel concentrations, and endothelial cell transport of cremophor-free, albumin-bound paclitaxel, ABI-007, compared with cremophor-based paclitaxel. [SEP] Justify:

Output: The text corroborates the claim by discussing various research articles that highlight the role of nanomaterials, such as fullerene derivatives and metallofullerene nanoparticle systems, in cancer treatment. Specifically, it mentions 'nanotechnology-based drug delivery systems' and applications of nanomaterials in 'cancer imaging and therapy,' which directly supports the development of nanomaterials for effective cancer treatments.


Input: Task: contrast the claim using the given text. Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: Therapy-based trials were the most effective because 83% (5/6) of the studies that assessed this intervention type found significant improvements in mental well-being outcomes [22,37-40], and only 17% (1/6) found mixed effects [35]. Full-abstinence interventions showed mixed effectiveness overall, with 42% (5/12) of them showing mixed effects [41,46,49-51], a third (4/12, 33%) showing no effect [42,43,45,47], and a quarter (3/12, 25%) showing a benefit of the intervention [36,44,48]. Social media use interventions that limited use also showed mixed effectiveness overall, with more than half (3/5, 60%) of the studies showing no effect [52,53,56] and 20% (1/5) showing an improvement [55] and mixed effects [54], respectively. Figure 3. Summary of the effectiveness of the different types of social media use interventions on mental well-being–related outcomes. DiscussionPrincipal FindingsThis review provides some evidence for the improvement of mental well-being in adults after social media use interventions. Of the 23 studies included in our analysis, 9 (39%) demonstrated improvements in mental well-being–related outcomes, with most of them (8/9, 89%) showing medium to large effect sizes. Depression was the most improved outcome overall, with 70% (7/10) of the studies that assessed depression showing improvement. Therapy-based interventions were the most effective, with 83% (5/6) of the studies evaluating these interventions showing improvement. Most of the studies (22/23, 96%) were of low quality, with significant issues related to selection bias and blinding affecting their quality. This review found that interventions that simply restrict social media use or impose full abstinence may not have as much benefit for mental well-being as therapy-based interventions. These interventions used established approaches such as counseling and CBT-based techniques to encourage mindfulness and reflection on how social media activity affects thoughts, emotions, and behavior. Therapy-based interventions may be more effective in causing behavior change in users than abstinence by enabling them to replace negative actions with structured goals and positive thinking and by providing motivation [58]. [SEP] Justify:

Output: The text contrasts the claim by indicating that social media use interventions have shown mixed effectiveness regarding mental well-being. It specifically states that interventions that simply restrict social media use or impose full abstinence may not yield significant benefits and that therapy-based approaches, which involve counseling and cognitive behavioral techniques, are more effective in improving mental well-being outcomes. This evidence suggests that social media algorithms do not inherently have a positive impact on mental well-being.


Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: The participants were pseudorandomly assigned to the two versions and two presentation orders for the booklets. StimuliThe target words, paragraphs, and assignment of items to versions and presentation orders (within the training booklets) were the same as in Experiments 1 and 2. The printed booklets containing the paragraphs were identical to those used in Experiment 2. Four worksheets were also devised for use during the training phase of the experiment. Each worksheet was designed to take approximately 30–45 min to complete. The order of the target words was randomized separately for each worksheet. 1 and 3, the participants were instructed to initially fill in as much as possible without the booklet, and then to refer to the booklet to complete any answers that they did not know. 2 and 4, they were instructed to use the booklet throughout the task. Worksheet 1 This two-page booklet contained a numbered list of the 36 target words, in a column on the left side, and a separate list of descriptions of the meanings of these words (e. g. , “Country that exports goods at low cost”), in a column on the right side. The participants’ task was to link each description with the appropriate word by writing down the appropriate number next to each description. Worksheet 2 The participants here generated a new example sentence for each target word that was compatible with its new definition. Worksheet 3 The third worksheet comprised a series of quiz questions about the paragraph (two questions per word; e. g. , “Where is a pouch normally found? ”). Worksheet 4 The final worksheet was a creative writing task. Participants were given a list of the 36 target words and were instructed to “tell a story” that included each of these words, at least once, using their new meanings. They could write as many sentences as they liked and could write in any style and on any subject. Procedure1, the participants came into the lab and read through the whole booklet of word meanings and completed Worksheet 1. The participants were then given the booklet of paragraphs to take home, together with Worksheets 2–4. They were instructed to complete one of these worksheets, in the correct order, on each of the next three consecutive days (Days 2–4) at home and in a quiet environment. [SEP] Justify:

Output: The text outlines a procedural description of an experiment involving participants linking words with their meanings and completing various worksheets. However, it does not directly address or support the claim regarding semantic memory, as it focuses instead on the methodology and tasks assigned to participants. Therefore, it is considered irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: Res 2006;12:1317–24. 10. 1158/1078-0432. CCR-05-1634Search in 148. . A pegylated liposomal platform: pharmacokinetics, pharmacodynamics, and toxicity in mice using doxorubicin as a model drug. J 2004;389:381–9. 10. 1254/jphs. FPJ04001XSearch in 149. . Albumin-bound formulation of paclitaxel (Abraxane ABI-007) in the treatment of breast cancer. Nanomed 2009;4:99–105. Search in 150. Park JW. Liposome-based drug delivery in breast cancer treatment. Res 2002;4:95–9. 10. 1186/bcr432Search in 151. Bae YH. Drug targeting and tumor heterogeneity. J 2009;133:2–3. 10. 1016/j. jconrel. 2008. 09. 074Search in 152. Regulation of transport pathways in tumor vessels: role of tumor type and microenvironment. 1998;95:4607–12. 10. 1073/pnas. 95. 8. 4607Search in 153. Gold nanop9. 10. 1016/j. biomaterials. 2011. 10. 058Search in 154. . Targeting strategies for multifunctional nanop44. 10. 7150/thno. 3463Search in 155. Liposomal vincristine in relapsed non-Hodgkin’s lymphomas: early results of an ongoing phase II trial. 2000;11:69–72. 10. 1023/A:1008348010437Search in 156. . Targeted delivery of albumin bound paclitaxel in the treatment of advanced breast cancer. Ther 2009;2:179–88. 10. 2147/OTT. S3863Search in 157. pharmacokinetic study of a weekly liposomal paclitaxel formulation (Genexol-PM) in patients with solid tumors. 2010;21:382–8. 10. 1093/annonc/mdp315Search in 158. Davis ME. The first targeted delivery of siRNA in humans via a nanop68. 10. 1021/mp900015ySearch in 159. [SEP] Justify:

Output: The text corroborates the claim by referencing various studies and research on nanomaterials and their applications in cancer treatment, such as the use of pegylated liposomes and albumin-bound formulations for drug delivery in breast cancer, indicating the ongoing development of nanomaterials aimed at improving cancer therapies.


Input: Task: contrast the claim using the given text. Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: Therapy-based interventions may also help to reduce FOMO by encouraging individuals to reevaluate life priorities, focus on other activities, and reduce social comparison and envy [36,39]. We found limiting social media use to be the least effective method. One hypothesis is that users would still have been exposed to social media during the trial and may have intensified their use owing to an awareness of a time restriction. This would have offset any potential positive improvement. Adherence to limiting social media use or abstaining from social media use may also have been challenging for participants, and adherence is difficult to track and measure across devices used to access social media [37]. In 1 study, 19. 4% (35/180) of the participants were excluded from analysis because they were unable to abstain from social media for >2 days, which may give an indication of compliance rates in these studies [42]. These findings overall suggest that health and care professionals, mental health charities, and public health bodies should encourage the use of therapy-based approaches to manage social media use rather than focusing on reducing time spent on social media. These interventions can also be relatively cost-effective because this review showed improvements in participants’ well-being after they used internet-based self-guided therapy-based interventions to manage problematic social media use. However, delivering therapy-based approaches to manage (problematic) social media use is currently limited owing to resource and time constraints in health and care systems. This review found that 3 (13%) of the 23 studies showed a reduction in some mental well-being–related outcomes after the intervention, such as life satisfaction and loneliness [35,50,51]. The causes for these findings could be due to methodological reasons because the authors of 1 (33%) of these 3 studies proposed that their study participants were unaware at the time of recruitment that abstinence from social media may be required [50], which may have made participants less receptive to the intervention and eliminated the beneficial consequences of abstinence that may have arisen in other studies. Previous research also suggests that reducing or limiting social media use can reduce mental well-being by causing a loss of social connection and increasing loneliness [9]. Some individuals are reported to find social connections easier to maintain over the web, with social media enabling users to preserve their relationships [59,60]. [SEP] Justify:

Output: The text contrasts the claim by discussing negative implications of social media use on mental well-being. It indicates that limiting social media use was found to be ineffective and suggests that therapy-based interventions may be more beneficial. Furthermore, it mentions that previous research shows reducing social media use can harm mental well-being by causing increased loneliness. This evidence directly disputes the claim that social media algorithms always have a positive impact, presenting a more nuanced view that highlights potential negative consequences.


Input: Task: pass the claim using the given text. Claim: Semantic memory is involved in understanding the meanings of words and sentences. [SEP] Text: 05], or Worksheet 4 [F 1(1, 34) = 0. 499, p >. 05; F 2(1, 14) = 0. 517, p >. 05]. Lexical decision taskOne participant was removed due to highly variable response times and an unusually high proportion of very slow responses (SD = 344, 19 % of responses greater than 1,000 ms). The remaining 15 participants made between 1. 7 % and 15. 4 % errors, with mean response times that ranged between 535 and 863 ms. One of the trained words (“snow”) was inadvertently omitted from the experiment, and two of the untrained words (“whack” and “gulp”) were removed because of error rates greater than 50 %. Only correct response times were included in the analyses. Individual responses that were greater than three standard deviations above the mean for the participant or shorter than 250 ms were excluded from the analysis (1. 5 % of the responses to the experimental items). The same analyses were conducted as in Experiment 2 (see Fig. 1). Responses to the trained words were both faster [F 1(1, 13) = 36. 9, p <. 001; F 2(1, 103) = 19. 2, p <. 001] and more accurate [F 1(1, 13) = 20. 0, p <. 001; F 2(1, 103) = 10. 2, p = <. 005] as compared with those for the untrained words. Within the set of trained items, response times were significantly faster for the related than for the unrelated words [F 1(1, 13) = 4. 9, p <. 05; F 2(1, 33) = 7. 5, p <. 01]. Participants were more accurate for the related words, although this difference was not significant [F 1(1, 13) = 1. 6, p >. 2; F 2(1, 33) = 1. 4, p >. 2]. These analyses were repeated using the subset of responses to those words for which an individual participant had responded correctly in the cued-recall task—that is, including only responses to words for which we had evidence that the participant had retained information about its new meaning. Footnote 3 These analyses showed the same significance patterns as the main analysis. [SEP] Justify:

Output: The text does not address the claim about semantic memory and its role in understanding meanings of words and sentences. Instead, it discusses experimental methods, participant responses, and statistical analyses related to lexical decision tasks, with no indication of how semantic memory contributes to language comprehension.


Input: Task: corroborate the claim using the given text. Claim: Nanomaterials are being developed for more effective cancer treatments. [SEP] Text: 201104763Search in 170. Multifunctional hybrid silica nanop18. 10. 1039/c2tb00223jSearch in 171. Persidis A. Cancer multidrug resistance. 1999;17:94–5. 10. 1038/5289Search in 172. Gottesman MM. Mechanisms of cancer drug resistance. Med 2002;53:615–27. 10. 1146/annurev. med. 53. 082901. 103929Search in 173. Peer D, Margalit R. Fluoxetine and reversal of multidrug resistance. 2006;237:180–7. 10. 1016/j. canlet. 2005. 06. 003Search in 174. Iversen T-G, Skotland T, Sandvig K. Endocytosis and intracellular transport of nanop85. 10. 1016/j. nantod. 2011. 02. 003Search in 175. . Nanomedicine for targeted cancer therapy: towards the overcoming of drug resistance. Updat 2011;14:150–63. 10. 1016/j. drup. 2011. 01. 003Search in 176. dose escalation and pharmacokinetic study of pluronic polymer-bound doxorubicin (SP1049C) in patients with advanced cancer. Cancer 2004;90:2085–91. 10. 1038/sj. bjc. 6601856Search in 177. A new polymer-lipid hybrid nanop85. 10. 1007/s11095-006-0282-xSearch in 178. -Pouessel A, Denizot B, et al. A new generation of anticancer, drug-loaded, colloidal vectors reverses multidrug resistance in glioma and reduces tumor progression in rats. Ther 2006;5:1710–22. 10. 1158/1535-7163. MCT-06-0289Search in 179. . Doxorubicin loaded pH-sensitive polymeric micelles for reversal of resistant MCF-7 tumor. J 2005;103:405–18. 10. 1016/j. jconrel. 2004. 12. 018Search in 180. Engineered design of mesoporous silica nanop50. 10. 1021/nn100690mSearch in 181. [SEP] Justify:

Output: The text corroborates the claim as it references multiple studies and developments regarding the use of nanomaterials, including 'nanomedicine for targeted cancer therapy' and 'a new generation of anticancer, drug-loaded, colloidal vectors.' These statements suggest that ongoing research is focused on the application of nanomaterials in enhancing cancer treatment effectiveness.