{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T03:44:38Z","timestamp":1777434278626,"version":"3.51.4"},"reference-count":62,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Argument &amp; Computation"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:p>Argumentation is the process of creating arguments for and against competing claims. Computational argumentation involves different ways of analyzing and reasoning upon arguments and their relations. More precisely, Argument Mining is the research field aiming at automatically identifying and classifying argument structures in text. The research field is mainly focussed on the extraction of explicit argument structures (i.e., claims and premises connected by support and attack relations). However, an even more challenging task consists in extracting implicit argument structures in text (e.g., enthymemes). These structures are particularly valuable to then address argument reasoning, e.g., on incomplete and uncertain information, to finally compute the set of acceptable arguments, i.e., argument justification and skepticism. In this paper, we present and compare current approaches and available datasets for the novel task of Implicit Argument Mining. Future work perspectives are discussed to pave the way to further studies in this direction.<\/jats:p>","DOI":"10.1177\/19462174251344764","type":"journal-article","created":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T04:37:20Z","timestamp":1751258240000},"page":"3-27","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Mining implicit arguments for reasoning: A survey"],"prefix":"10.1177","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-0272-3911","authenticated-orcid":false,"given":"Ekaterina","family":"Sviridova","sequence":"first","affiliation":[{"name":"Universit\u00e9 C\u00f4te d\u2019Azur, CNRS, Inria, I3S, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9374-7872","authenticated-orcid":false,"given":"Elena","family":"Cabrio","sequence":"additional","affiliation":[{"name":"Universit\u00e9 C\u00f4te d\u2019Azur, CNRS, Inria, I3S, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3495-493X","authenticated-orcid":false,"given":"Serena","family":"Villata","sequence":"additional","affiliation":[{"name":"Universit\u00e9 C\u00f4te d\u2019Azur, CNRS, Inria, I3S, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,6,30]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v38i3.2704"},{"key":"e_1_3_3_3_2","doi-asserted-by":"crossref","unstructured":"Cabrio E Villata S. Five years of argument mining: a data-driven analysis. In: Proceedings of the twenty-seventh international joint conference on artificial intelligence IJCAI-18 2018 pp.5427\u20135433. International Joint Conferences on Artificial Intelligence Organization.","DOI":"10.24963\/ijcai.2018\/766"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1162\/coli_a_00364"},{"key":"e_1_3_3_5_2","doi-asserted-by":"crossref","unstructured":"Wachsmuth H Naderi N Hou Y et\u00a0al. Computational argumentation quality assessment in natural language. In: Proceedings of the 15th conference of the European chapter of the Association for Computational Linguistics: volume 1 Long Papers (eds Lapata M Blunsom P and Koller A) 2017 pp.176\u2013187. Valencia Spain: Association for Computational Linguistics https:\/\/aclanthology.org\/E17-1017\/.","DOI":"10.18653\/v1\/E17-1017"},{"key":"e_1_3_3_6_2","doi-asserted-by":"crossref","unstructured":"Wang X Cabrio E Villata S. Argument and counter-argument generation: a critical survey. In: International conference on applications of natural language to information systems 2023 pp.500\u2013510. Springer.","DOI":"10.1007\/978-3-031-35320-8_37"},{"key":"e_1_3_3_7_2","doi-asserted-by":"crossref","unstructured":"Lawrence J Reed C. Argument mining using argumentation scheme structures. In: COMMA 2016.","DOI":"10.3233\/978-1-61499-686-6-379"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00525"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511802034"},{"key":"e_1_3_3_10_2","first-page":"2493","article-title":"Argumentation schemes. History, classifications, and computational applications","volume":"4","author":"Macagno F","year":"2017","unstructured":"Macagno F, Walton D, Reed C. Argumentation schemes. History, classifications, and computational applications. J Log Appl 2017; 4: 2493\u20132556.","journal-title":"J Log Appl"},{"key":"e_1_3_3_11_2","unstructured":"Hulpus I Kobbe J Meilicke C et\u00a0al. Towards explaining natural language arguments with background knowledge. In: PROFILES\/SEMEX@ISWC 2019."},{"key":"e_1_3_3_12_2","doi-asserted-by":"crossref","unstructured":"Rajendran P Bollegala D Parsons S. Contextual stance classification of opinions: a step towards enthymeme reconstruction in online reviews. In: Proceedings of the third workshop on argument mining 2016 pp.31\u201339. Berlin Germany: Association for Computational Linguistics.","DOI":"10.18653\/v1\/W16-2804"},{"key":"e_1_3_3_13_2","doi-asserted-by":"crossref","unstructured":"Stahl M D\u00fcsterhus N Chen M-H et\u00a0al. Mind the gap: automated corpus creation for enthymeme detection and reconstruction in learner arguments. In: Bouamor H Pino J and Bali K (eds) Findings of the Association for Computational Linguistics: EMNLP 2023. Singapore: Association for Computational Linguistics 2023 pp.4703\u20134717.","DOI":"10.18653\/v1\/2023.findings-emnlp.312"},{"key":"e_1_3_3_14_2","first-page":"1","article-title":"Finding enthymemes in real-world texts: a feasibility study","volume":"8","author":"Razuvayevskaya O","year":"2017","unstructured":"Razuvayevskaya O, Teufel S. Finding enthymemes in real-world texts: a feasibility study. Argum Comput 2017; 8: 1\u201317.","journal-title":"Argum Comput"},{"key":"e_1_3_3_15_2","doi-asserted-by":"crossref","unstructured":"Chakrabarty T Trivedi A Muresan S. Implicit premise generation with discourse-aware commonsense knowledge models. In: Proceedings of the 2021 conference on empirical methods in natural language processing (eds Moens M-F Huang X Specia L and Yih SW-t) 2021 pp.6247\u20136252. Online and Punta Cana Dominican Republic: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2021.emnlp-main.504"},{"key":"e_1_3_3_16_2","doi-asserted-by":"crossref","unstructured":"Habernal I Wachsmuth H Gurevych I et\u00a0al. The argument reasoning comprehension task: identification and reconstruction of implicit warrants. In: Proceedings of the 2018 conference of the NAACL Volume 1 (Long Papers) 2018 pp.1930\u20131940. New Orleans Louisiana: Association for Computational Linguistics.","DOI":"10.18653\/v1\/N18-1175"},{"key":"e_1_3_3_17_2","unstructured":"Becker M Korfhage K Frank A. Implicit knowledge in argumentative texts: an annotated corpus. In: Proceedings of the twelfth language resources and evaluation conference (eds Calzolari N B\u00e9chet F Blache P Choukri K Cieri C Declerck T Goggi S Isahara H Maegaard B Mariani J Mazo H Moreno A Odijk J and Piperidis S) 2020 pp.2316\u20132324. Marseille France: European Language Resources Association."},{"key":"e_1_3_3_18_2","doi-asserted-by":"crossref","unstructured":"Cabrio E Tonelli S Villata S. From discourse analysis to argumentation schemes and back: relations and differences. In: Leite J Son TC Torroni P van der Torre L and Woltran S (eds) Computational logic in multi-agent systems. Berlin Heidelberg: Springer Berlin Heidelberg 2013 pp.1\u201317.","DOI":"10.1007\/978-3-642-40624-9_1"},{"key":"e_1_3_3_19_2","first-page":"1","article-title":"From argument diagrams to argumentation mining in texts: a survey","volume":"7","author":"Peldszus A","year":"2013","unstructured":"Peldszus A, Stede M. From argument diagrams to argumentation mining in texts: a survey. Int J Cognit Inform Natl Intell 2013; 7: 1\u201331.","journal-title":"Int J Cognit Inform Natl Intell"},{"key":"e_1_3_3_20_2","unstructured":"Stede M Afantenos S Peldszus A et\u00a0al. Parallel discourse annotations on a corpus of short texts. In: Proceedings of the tenth international conference on language resources and evaluation (LREC\u201916) 2016 pp.1051\u20131058. Portoro\u017e Slovenia: ELRA."},{"key":"e_1_3_3_21_2","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511840005"},{"key":"e_1_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-007-0357-5"},{"key":"e_1_3_3_23_2","unstructured":"Wang J. On freeman\u2019s argument structure approach. In: Chinese conference on logic and argumentation 2016 https:\/\/api.semanticscholar.org\/CorpusID:8638296."},{"key":"e_1_3_3_24_2","doi-asserted-by":"crossref","unstructured":"Alshomary M Syed S Potthast M et\u00a0al. Target inference in argument conclusion generation. In: Proceedings of the 58th Annual meeting of the Association for Computational Linguistics (eds Jurafsky D Chai J Schluter N and Tetreault J) 2020 pp.4334\u20134345. Association for Computational Linguistics.","DOI":"10.18653\/v1\/2020.acl-main.399"},{"key":"e_1_3_3_25_2","doi-asserted-by":"crossref","unstructured":"Singh K Reisert P Inoue N et\u00a0al. Improving evidence detection by leveraging warrants. In: Proceedings of the second workshop on fact extraction and verification 2019 pp.57\u201362. Hong Kong China.","DOI":"10.18653\/v1\/D19-6610"},{"key":"e_1_3_3_26_2","doi-asserted-by":"crossref","unstructured":"Hidey C Musi E Hwang A et\u00a0al. Analyzing the semantic types of claims and premises in an online persuasive forum. In: Proceedings of the 4th workshop on argument mining 2017 pp.11\u201321. Copenhagen Denmark: Association for Computational Linguistics.","DOI":"10.18653\/v1\/W17-5102"},{"key":"e_1_3_3_27_2","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007846431353"},{"key":"e_1_3_3_28_2","doi-asserted-by":"publisher","DOI":"10.2307\/25655298"},{"key":"e_1_3_3_29_2","first-page":"1","article-title":"What types of arguments are there?","volume":"51","author":"Freeman JB","year":"2013","unstructured":"Freeman JB. What types of arguments are there? OSSA Conf Arch 2013; 51: 1\u201315.","journal-title":"OSSA Conf Arch"},{"key":"e_1_3_3_30_2","first-page":"41","article-title":"Logic and conversation","volume":"3","author":"Grice P","year":"1975","unstructured":"Grice P. Logic and conversation. Synt Semant 1975; 3: 41\u201358.","journal-title":"Synt Semant"},{"key":"e_1_3_3_31_2","doi-asserted-by":"publisher","DOI":"10.2307\/j.ctvpj74xx"},{"key":"e_1_3_3_32_2","first-page":"1","article-title":"Argument schemes \u2013 an epistemological approach","volume":"17","author":"Lumer C","year":"2011","unstructured":"Lumer C, Dove IJ. Argument schemes \u2013 an epistemological approach. OSSA Conf Archive 2011; 17: 1\u201332.","journal-title":"OSSA Conf Archive"},{"key":"e_1_3_3_33_2","volume-title":"A systematic theory of argumentation: the pragma-dialectical approach","author":"van Eemeren F","year":"2004","unstructured":"van Eemeren F, Grootendorst R, Grootendorst R. A systematic theory of argumentation: the pragma-dialectical approach. Cambridge University Press, 2004."},{"key":"e_1_3_3_34_2","doi-asserted-by":"crossref","unstructured":"Saadat-Yazdi A Pan JZ Kokciyan N. Uncovering implicit inferences for improved relational argument mining. In: Proceedings of the 17th conference of the European chapter of the Association for Computational Linguistics (eds Vlachos A and Augenstein I) 2023 pp.2484\u20132495. Dubrovnik Croatia: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2023.eacl-main.182"},{"key":"e_1_3_3_35_2","doi-asserted-by":"crossref","unstructured":"Becker M Staniek M Nastase V et\u00a0al. Enriching argumentative texts with implicit knowledge. In: Natural language processing and information systems \u2013 22nd international conference on applications of natural language to information systems NLDB 2017 Li\u00e8ge Belgium proceedings Volume 10260 Lecture Notes in Computer Science (eds Frasincar F Ittoo A Nguyen LM and M\u00e9tais E) 2017 pp.84\u201396. Springer.","DOI":"10.1007\/978-3-319-59569-6_9"},{"key":"e_1_3_3_36_2","doi-asserted-by":"crossref","unstructured":"Boltu\u017ei\u0107 F \u0160najder J. Fill the gap! Analyzing implicit premises between claims from online debates. In: Proceedings of the third workshop on argument mining 2016 pp.124\u2013133. Berlin Germany: Association for Computational Linguistics.","DOI":"10.18653\/v1\/W16-2815"},{"key":"e_1_3_3_37_2","doi-asserted-by":"crossref","unstructured":"Wachsmuth H Trenkmann M Stein B et\u00a0al. A review corpus for argumentation analysis. In: Conference on intelligent text processing and computational linguistics 2014 pp.115\u2013127. Berlin Heidelberg: Springer Berlin Heidelberg.","DOI":"10.1007\/978-3-642-54903-8_10"},{"key":"e_1_3_3_38_2","volume-title":"International corpus of learner English. Version 3","author":"Granger S","year":"2020","unstructured":"Granger S, Dupont M, Meunier F, et al. International corpus of learner English. Version 3. Louvain-la-Neuve: Presses universitaires de Louvain, 2020."},{"key":"e_1_3_3_39_2","unstructured":"Bhagavatula C Bras RL Malaviya C et\u00a0al. Abductive commonsense reasoning. In: 8th International conference on learning representations ICLR 2020 2020 Addis Ababa Ethiopia. OpenReview.net."},{"key":"e_1_3_3_40_2","unstructured":"Peldszus A. An annotated corpus of argumentative microtexts. In: First European conference on argumentation: argumentation and reasoned action 2015 Lisbon Portugal."},{"key":"e_1_3_3_41_2","doi-asserted-by":"crossref","unstructured":"Choi H Lee H. GIST at SemEval-2018 task 12: a network transferring inference knowledge to argument reasoning comprehension task. In: Proceedings of the 12th international workshop on semantic evaluation. (eds Apidianaki M Mohammad S M May J Shutova E Bethard S and Carpuat M) 2018 pp.773\u2013777. New Orleans Louisiana: Association for Computational Linguistics.","DOI":"10.18653\/v1\/S18-1122"},{"key":"e_1_3_3_42_2","doi-asserted-by":"crossref","unstructured":"Bowman SR Angeli G Potts C et\u00a0al. A large annotated corpus for learning natural language inference. In: Proceedings of the 2015 conference on empirical methods in natural language processing (eds M\u00e0rquez L Callison-Burch C and Su J) 2015 pp.632\u2013642. Lisbon Portugal: Association for Computational Linguistics.","DOI":"10.18653\/v1\/D15-1075"},{"key":"e_1_3_3_43_2","doi-asserted-by":"crossref","unstructured":"Williams A Nangia N Bowman S. A broad-coverage challenge corpus for sentence understanding through inference. In: Proceedings of the 2018 conference of the North American chapter of the Association for Computational Linguistics: human language technologies Volume 1 (Long Papers) (eds Walker M Ji H and Stent A) 2018 pp.1112\u20131122. New Orleans Louisiana: Association for Computational Linguistics. DOI: https:\/\/doi.org\/10.18653\/v1\/N18-1101. https:\/\/aclanthology.org\/N18-1101\/.","DOI":"10.18653\/v1\/N18-1101"},{"key":"e_1_3_3_44_2","doi-asserted-by":"crossref","unstructured":"Rinott R Dankin L Alzate Perez C et\u00a0al. Show me your evidence \u2013 an automatic method for context dependent evidence detection. In: Proceedings of the 2015 conference on empirical methods in natural language processing (eds M\u00e0rquez L Callison-Burch C and Su J) 2015 pp.440\u2013450. Lisbon Portugal: Association for Computational Linguistics.","DOI":"10.18653\/v1\/D15-1050"},{"key":"e_1_3_3_45_2","doi-asserted-by":"crossref","unstructured":"Bar-Haim R Bhattacharya I Dinuzzo F et\u00a0al. Stance classification of context-dependent claims. In: Proceedings of the 15th conference of the European chapter of the Association for Computational Linguistics: volume 1 Long Papers (eds Lapata M Blunsom P and Koller A) 2017 pp.251\u2013261. Valencia Spain: Association for Computational Linguistics.","DOI":"10.18653\/v1\/E17-1024"},{"key":"e_1_3_3_46_2","doi-asserted-by":"crossref","unstructured":"Wang L Ling W. Neural network-based abstract generation for opinions and arguments. In: Proceedings of the 2016 conference of the North American chapter of the Association for Computational Linguistics: human language technologies (eds Knight K Nenkova A and Rambow O) 2016 pp.47\u201357. San Diego CA: ACL. https:\/\/aclanthology.org\/N16-1007.","DOI":"10.18653\/v1\/N16-1007"},{"key":"e_1_3_3_47_2","doi-asserted-by":"crossref","unstructured":"Stab C Gurevych I. Identifying argumentative discourse structures in persuasive essays. In: Proceedings of the 2014 conference on empirical methods in natural language processing 2014 pp.46\u201356. Doha Qatar.","DOI":"10.3115\/v1\/D14-1006"},{"key":"e_1_3_3_48_2","unstructured":"Wojatzki M Zesch T. Stance-based argument mining \u2013 modeling implicit argumentation using stance. In: Conference on natural language processing 2016. https:\/\/api.semanticscholar.org\/CorpusID:85555944."},{"key":"e_1_3_3_49_2","doi-asserted-by":"crossref","unstructured":"Mohammad S Kiritchenko S Sobhani P et\u00a0al. SemEval-2016 task 6: detecting stance in tweets. In: Proceedings of the 10th international workshop on semantic evaluation (SemEval-2016) (eds Bethard S Carpuat M Cer D Jurgens D Nakov P and Zesch T) 2016 pp.31\u201341. San Diego California: Association for Computational Linguistics.","DOI":"10.18653\/v1\/S16-1003"},{"key":"e_1_3_3_50_2","doi-asserted-by":"crossref","unstructured":"Paul D Opitz J Becker M et\u00a0al. Argumentative relation classification with background knowledge. In: COMMA 2020.","DOI":"10.3233\/FAIA200515"},{"key":"e_1_3_3_51_2","doi-asserted-by":"crossref","unstructured":"Opitz J Frank A. Dissecting content and context in argumentative relation analysis. In: Proceedings of the 6th workshop on argument mining (eds Stein B and Wachsmuth H) 2019 pp.25\u201334. Florence Italy: Association for Computational Linguistics.","DOI":"10.18653\/v1\/W19-4503"},{"key":"e_1_3_3_52_2","doi-asserted-by":"crossref","unstructured":"Mestre R Milicin R Middleton SE et\u00a0al. M-arg: multimodal argument mining dataset for political debates with audio and transcripts. In: Proceedings of the 8th workshop on argument mining 2021 pp.78\u201388. Punta Cana: Dominican Republic.","DOI":"10.18653\/v1\/2021.argmining-1.8"},{"key":"e_1_3_3_53_2","doi-asserted-by":"crossref","unstructured":"Sviridova E Yeginbergen A Estarrona A et\u00a0al. CasiMedicos-arg: a medical question answering dataset annotated with explanatory argumentative structures. In: Proceedings of the 2024 conference on empirical methods in natural language processing (eds Al-Onaizan Y Bansal M and Chen Y-N) 2024 pp.18463\u201318475. Miami Florida USA: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2024.emnlp-main.1026"},{"key":"e_1_3_3_54_2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkaa1043"},{"key":"e_1_3_3_55_2","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkh061"},{"key":"e_1_3_3_56_2","unstructured":"Vaswani A Shazeer NM Parmar N et\u00a0al. Attention is all you need. In: Neural information processing systems (NIPS) 2017 Long Beach CA USA."},{"key":"e_1_3_3_57_2","doi-asserted-by":"crossref","unstructured":"Delas Z Pl\u00fcss B Ruiz-Dolz R. An argumentation scheme-based framework for automatic reconstruction of natural language enthymemes. In: COMMA Frontiers in Artificial Intelligence and Applications 2024 pp.61\u201372.","DOI":"10.3233\/FAIA240310"},{"key":"e_1_3_3_58_2","unstructured":"Speer R Havasi C. Representing general relational knowledge in ConceptNet 5. In: Proceedings of the eighth international conference on language resources and evaluation (LREC\u201812) (eds Calzolari N Choukri K Declerck T Do\u011fan MU Maegaard B Mariani J Moreno A Odijk J and Piperidis S) 2012 pp.3679\u20133686. Istanbul Turkey: European Language Resources Association (ELRA)."},{"key":"e_1_3_3_59_2","doi-asserted-by":"crossref","unstructured":"Becker M Liang S Frank A. Reconstructing implicit knowledge with language models. In: Proceedings of deep learning inside out (DeeLIO): the 2nd workshop on knowledge extraction and integration for deep learning architectures. (eds Agirre E Apidianaki M and Vuli\u0107 I) 2021 pp.11\u201324. Association for Computational Linguistics.","DOI":"10.18653\/v1\/2021.deelio-1.2"},{"key":"e_1_3_3_60_2","doi-asserted-by":"crossref","unstructured":"Tan C Niculae V Danescu-Niculescu-Mizil C et\u00a0al. Winning arguments: interaction dynamics and persuasion strategies in good-faith online discussions. In: Proceedings of the 25th international conference on world wide web 2016.","DOI":"10.1145\/2872427.2883081"},{"key":"e_1_3_3_61_2","doi-asserted-by":"crossref","unstructured":"Kawarada M Hirao T Uchida W et\u00a0al. Argument mining as a text-to-text generation task. In: Proceedings of the 18th conference of the European chapter of the Association for Computational Linguistics (Volume 1: Long Papers) (eds Graham Y and Purver M) 2024 pp.2002\u20132014. St. Julian\u2019s Malta: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2024.eacl-long.121"},{"key":"e_1_3_3_62_2","doi-asserted-by":"crossref","unstructured":"Alshomary M Wachsmuth H. Conclusion-based counter-argument generation. In: Proceedings of the 17th conference of the European chapter of the Association for Computational Linguistics (eds Vlachos A and Augenstein I) 2023 pp.957\u2013967. Dubrovnik Croatia: Association for Computational Linguistics.","DOI":"10.18653\/v1\/2023.eacl-main.67"},{"key":"e_1_3_3_63_2","unstructured":"Chiang W Zheng L Sheng Y et\u00a0al. Chatbot arena: an open platform for evaluating llms by human preference. CoRR abs\/2403.04132 2024."}],"container-title":["Argument &amp; Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/19462174251344764","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/19462174251344764","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/19462174251344764","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T11:53:31Z","timestamp":1777377211000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/19462174251344764"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":62,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["10.1177\/19462174251344764"],"URL":"https:\/\/doi.org\/10.1177\/19462174251344764","relation":{},"ISSN":["1946-2166","1946-2174"],"issn-type":[{"value":"1946-2166","type":"print"},{"value":"1946-2174","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,30]]}}}