{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T13:13:12Z","timestamp":1740143592832,"version":"3.37.3"},"reference-count":58,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,6,2]],"date-time":"2023-06-02T00:00:00Z","timestamp":1685664000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,6,2]],"date-time":"2023-06-02T00:00:00Z","timestamp":1685664000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100003023","name":"Minist\u00e8re de l\u2019\u00c9ducation Nationale","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100003023","id-type":"DOI","asserted-by":"crossref"}]},{"name":"research england, in the form of the expanding excellence in england programme"},{"DOI":"10.13039\/501100000266","name":"engineering and physical sciences research council","doi-asserted-by":"publisher","award":["EP\/T02450X\/1"],"award-info":[{"award-number":["EP\/T02450X\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Lang Resources & Evaluation"],"published-print":{"date-parts":[[2024,3]]},"DOI":"10.1007\/s10579-023-09664-1","type":"journal-article","created":{"date-parts":[[2023,6,2]],"date-time":"2023-06-02T12:52:49Z","timestamp":1685710369000},"page":"175-201","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Assessing linguistic generalisation in language models: a dataset for Brazilian Portuguese"],"prefix":"10.1007","volume":"58","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4366-1215","authenticated-orcid":false,"given":"Rodrigo","family":"Wilkens","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6101-0814","authenticated-orcid":false,"given":"Leonardo","family":"Zilio","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3731-9168","authenticated-orcid":false,"given":"Aline","family":"Villavicencio","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,6,2]]},"reference":[{"key":"9664_CR1","doi-asserted-by":"crossref","unstructured":"Abdaoui, A., Pradel, C., & Sigel, G. (2020). Load what you need: Smaller versions of mutililingual bert. In Proceedings of SustaiNLP: Workshop on Simple and Efficient Natural Language Processing, pp. 119\u2013123.","DOI":"10.18653\/v1\/2020.sustainlp-1.16"},{"key":"9664_CR2","unstructured":"Bacon, G., & Regier, T. (2019). Does bert agree? Evaluating knowledge of structure dependence through agreement relations. arXiv:1908.09892."},{"key":"9664_CR3","unstructured":"Bakarov, A. (2018). A survey of word embeddings evaluation methods. arXiv:1801.09536."},{"key":"9664_CR4","unstructured":"Bolukbasi, T., Chang, K.-W., Zou, J., Saligrama, V., & Kalai, A. (2016). Man is to computer programmer as woman is to homemaker? Debiasing word embeddings. In Proceedings of the 30th International Conference on Neural Information Processing Systems, NIPS\u201916, Curran Associates Inc., pp. 4356\u20134364,"},{"key":"9664_CR5","doi-asserted-by":"crossref","unstructured":"Conneau, A., Khandelwal, K., Goyal, N., Chaudhary, V., Wenzek, G., Guzm\u00e1n, F., Grave, E., Ott, M., Zettlemoyer, L., & Stoyanov, V. (2019). Unsupervised cross-lingual representation learning at scale. arXiv:1911.02116.","DOI":"10.18653\/v1\/2020.acl-main.747"},{"issue":"4","key":"9664_CR6","doi-asserted-by":"publisher","first-page":"837","DOI":"10.1162\/COLI_a_00302","volume":"43","author":"M Constant","year":"2017","unstructured":"Constant, M., Eryi\u011fit, G., Monti, J., van der Plas, L., Ramisch, C., Rosner, M., & Todirascu, A. (2017). Multiword expression processing: A survey. Computational Linguistics, 43(4), 837\u2013892.","journal-title":"Computational Linguistics"},{"issue":"1","key":"9664_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1162\/coli_a_00341","volume":"45","author":"S Cordeiro","year":"2019","unstructured":"Cordeiro, S., Villavicencio, A., Idiart, M., & Ramisch, C. (2019). Unsupervised compositionality prediction of nominal compounds. Computational Linguistics, 45(1), 1\u201357.","journal-title":"Computational Linguistics"},{"key":"9664_CR8","unstructured":"De\u00a0Beaugrande, R.-A., & Dressler, W. U. (2011). Einf\u00fchrung in die textlinguistik. In Einf\u00fchrung in die Textlinguistik. Max Niemeyer Verlag."},{"key":"9664_CR9","unstructured":"Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv:1810.04805."},{"key":"9664_CR10","doi-asserted-by":"crossref","unstructured":"Dinan, E., Fan, A., Wu, L., Weston, J., Kiela, D., & Williams, A. (2020). Multi-dimensional gender bias classification. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 314\u2013331.","DOI":"10.18653\/v1\/2020.emnlp-main.23"},{"key":"9664_CR11","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1162\/tacl_a_00298","volume":"8","author":"A Ettinger","year":"2020","unstructured":"Ettinger, A. (2020). What BERT is not: Lessons from a new suite of psycholinguistic diagnostics for language models. Transactions of the Association for Computational Linguistics, 8, 34\u201348.","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"9664_CR12","doi-asserted-by":"crossref","unstructured":"Garcia, M., Kramer Vieira, T., Scarton, C., Idiart, M., & Villavicencio, A. (2021a). Assessing the representations of idiomaticity in vector models with a noun compound dataset labeled at type and token levels. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics, , pp. 2730\u20132741.","DOI":"10.18653\/v1\/2021.acl-long.212"},{"key":"9664_CR13","doi-asserted-by":"crossref","unstructured":"Garcia, M., Kramer\u00a0Vieira, T., Scarton, C., Idiart, M., & Villavicencio, A. (2021b). Probing for idiomaticity in vector space models. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. Association for Computational Linguistics, , pp. 3551\u20133564.","DOI":"10.18653\/v1\/2021.eacl-main.310"},{"key":"9664_CR14","unstructured":"Goldberg, Y. (2019). Assessing bert\u2019s syntactic abilities. arXiv:1901.05287."},{"issue":"2","key":"9664_CR15","doi-asserted-by":"publisher","first-page":"193","DOI":"10.3758\/BF03195564","volume":"36","author":"AC Graesser","year":"2004","unstructured":"Graesser, A. C., McNamara, D. S., Louwerse, M. M., & Cai, Z. (2004). Coh-metrix: Analysis of text on cohesion and language. Behavior Research Methods, Instruments, & Computers, 36(2), 193\u2013202.","journal-title":"Behavior Research Methods, Instruments, & Computers"},{"key":"9664_CR16","doi-asserted-by":"crossref","unstructured":"Gulordava, K., Bojanowski, P., Grave, \u00c9., Linzen, T., & Baroni, M. (2018). Colorless green recurrent networks dream hierarchically. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pp. 1195\u20131205.","DOI":"10.18653\/v1\/N18-1108"},{"key":"9664_CR17","doi-asserted-by":"publisher","DOI":"10.4324\/9781315836010","volume-title":"Cohesion in English","author":"MAK Halliday","year":"2014","unstructured":"Halliday, M. A. K., & Hasan, R. (2014). Cohesion in English. London: Routledge."},{"key":"9664_CR18","doi-asserted-by":"crossref","unstructured":"Kassner, N., & Sch\u00fctze, H. (2020). Negated and misprimed probes for pretrained language models: Birds can talk, but cannot fly. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, pp. 7811\u20137818.","DOI":"10.18653\/v1\/2020.acl-main.698"},{"key":"9664_CR19","unstructured":"Kilgarriff, A., Rychly, P., Smrz, P., & Tugwel, D. (2004). The sketch engine. In Proceedings of the Eleventh EURALEX International Congress."},{"key":"9664_CR20","first-page":"73","volume":"15","author":"IGV Koch","year":"1988","unstructured":"Koch, I. G. V. (1988). Principais mecanismos de coes\u00e3o textual em portugu\u00eas. Cadernos de Estudos Lingu\u00edsticos, 15, 73\u201380.","journal-title":"Cadernos de Estudos Lingu\u00edsticos"},{"key":"9664_CR21","volume-title":"A coes\u00e3o textual","author":"IGV Koch","year":"1999","unstructured":"Koch, I. G. V. (1999). A coes\u00e3o textual. London: Editora Contexto."},{"key":"9664_CR22","doi-asserted-by":"publisher","first-page":"486","DOI":"10.1162\/tacl_a_00327","volume":"8","author":"V Kumar","year":"2020","unstructured":"Kumar, V., Bhotia, T. S., Kumar, V., & Chakraborty, T. (2020). Nurse is closer to woman than surgeon? Mitigating gender-biased proximities in word embeddings. Transactions of the Association for Computational Linguistics, 8, 486\u2013503.","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"9664_CR23","doi-asserted-by":"crossref","unstructured":"Kurita, K., Vyas, N., Pareek, A., Black, A. W., & Tsvetkov, Y. (2019). Quantifying social biases in contextual word representations. In 1st ACL Workshop on Gender Bias for Natural Language Processing.","DOI":"10.18653\/v1\/W19-3823"},{"key":"9664_CR24","unstructured":"Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., & Soricut, R. (2019). ALBERT: A lite BERT for self-supervised learning of language representations. CoRR, arXiv:1909.11942."},{"key":"9664_CR25","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1162\/tacl_a_00115","volume":"4","author":"T Linzen","year":"2016","unstructured":"Linzen, T., Dupoux, E., & Goldberg, Y. (2016). Assessing the ability of lstms to learn syntax-sensitive dependencies. Transactions of the Association for Computational Linguistics, 4, 521\u2013535.","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"9664_CR26","unstructured":"Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., & Stoyanov, V. (2019). Roberta: A robustly optimized bert pretraining approach. arXiv:1907.11692."},{"key":"9664_CR27","doi-asserted-by":"crossref","unstructured":"Louwerse, M. (2002). An analytic and cognitive parameterization of coherence relations.","DOI":"10.1515\/cogl.2002.005"},{"key":"9664_CR28","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.jml.2016.04.001","volume":"92","author":"P Mandera","year":"2017","unstructured":"Mandera, P., Keuleers, E., & Brysbaert, M. (2017). Explaining human performance in psycholinguistic tasks with models of semantic similarity based on prediction and counting\u202f: a review and empirical validation. Journal of Memory and Language, 92, 57\u201378.","journal-title":"Journal of Memory and Language"},{"key":"9664_CR29","unstructured":"Marcus, G. (2020). The next decade in AI: four steps towards robust artificial intelligence. CoRR, arXiv:2002.06177."},{"key":"9664_CR30","doi-asserted-by":"crossref","unstructured":"Marvin, R., & Linzen, T. (2018). Targeted syntactic evaluation of language models. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 1192\u20131202.","DOI":"10.18653\/v1\/D18-1151"},{"issue":"4","key":"9664_CR31","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1093\/ijl\/3.4.235","volume":"3","author":"GA Miller","year":"1990","unstructured":"Miller, G. A., Beckwith, R., Fellbaum, C., Gross, D., & Miller, K. J. (1990). Introduction to wordnet: An on-line lexical database. International Journal of Lexicography, 3(4), 235\u2013244.","journal-title":"International Journal of Lexicography"},{"key":"9664_CR32","doi-asserted-by":"crossref","unstructured":"Mueller, A., Nicolai, G., Petrou-Zeniou, P., Talmina, N., & Linzen, T. (2020). Cross-linguistic syntactic evaluation of word prediction models. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 5523\u20135539.","DOI":"10.18653\/v1\/2020.acl-main.490"},{"key":"9664_CR33","unstructured":"Muniz, M. C., Maria das Gra\u00e7as, V. N., & Laporte, E. (2005). Unitex-pb, a set of flexible language resources for brazilian portuguese. In Workshop on Technology on Information and Human Language (TIL), pp. 2059\u20132068."},{"key":"9664_CR34","unstructured":"Nivre, J., Agi\u0107, \u017d., Ahrenberg, L., Antonsen, L., Aranzabe, M.\u00a0J., Asahara, M., Ateyah, L., Attia, M., Atutxa, A., Augustinus, L., & others (2017). Universal dependencies 2.1."},{"key":"9664_CR35","unstructured":"Oshikawa, R., Qian, J., & Wang, W. Y. (2020). A survey on natural language processing for fake news detection. In Proceedings of the 12th Language Resources and Evaluation Conference, pp. 6086\u20136093."},{"key":"9664_CR36","doi-asserted-by":"crossref","unstructured":"Pasquer, C., Savary, A., Ramisch, C., & Antoine, J.-Y. (2020). Verbal multiword expression identification: Do we need a sledgehammer to crack a nut? In Proceedings of the 28th International Conference on Computational Linguistics. International Committee on Computational Linguistics, pp. 3333\u20133345.","DOI":"10.18653\/v1\/2020.coling-main.296"},{"key":"9664_CR37","volume-title":"Gram\u00e1tica do portugu\u00eas brasileiro","author":"MA Perini","year":"2010","unstructured":"Perini, M. A. (2010). Gram\u00e1tica do portugu\u00eas brasileiro. London: Par\u00e1bola Ed."},{"key":"9664_CR38","doi-asserted-by":"crossref","unstructured":"Sag, I.\u00a0A., Baldwin, T., Bond, F., Copestake, A., & Flickinger, D. (2002). Multiword expressions: A pain in the neck for NLP. In Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing (CICLing 2002). Springer, pp. 1\u201315.","DOI":"10.1007\/3-540-45715-1_1"},{"issue":"2","key":"9664_CR39","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1162\/coli_a_00376","volume":"46","author":"GG \u015eahin","year":"2020","unstructured":"\u015eahin, G. G., Vania, C., Kuznetsov, I., & Gurevych, I. (2020). LINSPECTOR: Multilingual probing tasks for word representations. Computational Linguistics, 46(2), 335\u2013385.","journal-title":"Computational Linguistics"},{"key":"9664_CR40","unstructured":"Sanh, V., Debut, L., Chaumond, J., & Wolf, T. (2019). Distilbert, a distilled version of bert: Smaller, faster, cheaper and lighter. arXiv:1910.01108."},{"key":"9664_CR41","first-page":"0","volume":"708","author":"TB Sardinha","year":"2010","unstructured":"Sardinha, T. B. (2010). Corpus brasileiro. Inform\u00e1tica, 708, 0\u20131.","journal-title":"Inform\u00e1tica"},{"key":"9664_CR42","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1162\/tacl_a_00401","volume":"9","author":"B Savoldi","year":"2021","unstructured":"Savoldi, B., Gaido, M., Bentivogli, L., Negri, M., & Turchi, M. (2021). Gender bias in machine translation. Transactions of the Association for Computational Linguistics, 9, 845\u2013874.","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"9664_CR43","unstructured":"Scarton, C., & Alu\u0131sio, S. M. (2010). Coh-metrix-port: A readability assessment tool for texts in brazilian portuguese. In Proceedings of the 9th International Conference on Computational Processing of the Portuguese Language, Extended Activities Proceedings, PROPOR, vol.\u00a010."},{"key":"9664_CR44","doi-asserted-by":"crossref","unstructured":"Schneider, E. T.\u00a0R., de\u00a0Souza, J. V.\u00a0A., Knafou, J., Oliveira, L. E. S.\u00a0e., Copara, J., Gumiel, Y.\u00a0B., Oliveira, L. F. A.\u00a0d., Paraiso, E.\u00a0C., Teodoro, D., & Barra, C. M. C.\u00a0M. (2020). BioBERTpt: A Portuguese neural language model for clinical named entity recognition. In Proceedings of the 3rd Clinical Natural Language Processing Workshop. Association for Computational Linguistics, pp. 65\u201372.","DOI":"10.18653\/v1\/2020.clinicalnlp-1.7"},{"key":"9664_CR45","doi-asserted-by":"crossref","unstructured":"Scholivet, M., & Ramisch, C. (2017). Identification of ambiguous multiword expressions using sequence models and lexical resources. In Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017). Association for Computational Linguistics, pp. 167\u2013175.","DOI":"10.18653\/v1\/W17-1723"},{"key":"9664_CR46","unstructured":"Schrimpf, M., Blank, I., Tuckute, G., Kauf, C., Hosseini, E.\u00a0A., Kanwisher, N., Tenenbaum, J., & Fedorenko, E. (2020). Artificial neural networks accurately predict language processing in the brain. BioRxiv."},{"key":"9664_CR47","unstructured":"Souza, F., Nogueira, R., & Lotufo, R. (2019). Portuguese named entity recognition using bert-crf. arXiv:1909.10649."},{"key":"9664_CR48","doi-asserted-by":"crossref","unstructured":"Souza, F., Nogueira, R., & Lotufo, R. (2020). BERTimbau: pretrained BERT models for Brazilian Portuguese. In Brazilian Conference on Intelligent Systems. Springer, pp. 403\u2013417.","DOI":"10.1007\/978-3-030-61377-8_28"},{"key":"9664_CR49","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2991\/nlpr.d.200522.001","volume":"1","author":"Q Su","year":"2020","unstructured":"Su, Q., Wan, M., Liu, X., & Huang, C.-R. (2020). Motivations, methods and metrics of misinformation detection: An nlp perspective. Natural Language Processing Research, 1, 1\u201313.","journal-title":"Natural Language Processing Research"},{"key":"9664_CR50","unstructured":"Sylak-Glassman, J. (2016). The composition and use of the universal morphological feature schema (unimorph schema). Johns Hopkins University."},{"key":"9664_CR51","doi-asserted-by":"crossref","unstructured":"Tayyar\u00a0Madabushi, H., Gow-Smith, E., Garcia, M., Scarton, C., Idiart, M., & Villavicencio, A. (2022). SemEval-2022 task 2: Multilingual idiomaticity detection and sentence embedding. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022). Association for Computational Linguistics, pp. 107\u2013121.","DOI":"10.18653\/v1\/2022.semeval-1.13"},{"key":"9664_CR52","doi-asserted-by":"crossref","unstructured":"Tayyar\u00a0Madabushi, H., Gow-Smith, E., Scarton, C., & Villavicencio, A. (2021). AStitchInLanguageModels: Dataset and methods for the exploration of idiomaticity in pre-trained language models. In Findings of the Association for Computational Linguistics: EMNLP 2021. Association for Computational Linguistics, pp. 3464\u20133477.","DOI":"10.18653\/v1\/2021.findings-emnlp.294"},{"key":"9664_CR53","unstructured":"Vale, O., & Baptista, J. (2015). Novo dicion\u00e1rio de formas flexionadas do unitex-pb: Avalia\u00e7\u00e3o da flex\u00e3o verbal (new dictionary of inflected forms of unitex-pb: Evaluation of verbal inflection). In Proceedings of the 10th Brazilian Symposium in Information and Human Language Technology, pp. 171\u2013180."},{"issue":"4","key":"9664_CR54","doi-asserted-by":"publisher","first-page":"847","DOI":"10.1162\/coli_a_00391","volume":"46","author":"I Vuli\u0107","year":"2020","unstructured":"Vuli\u0107, I., Baker, S., Ponti, E. M., Petti, U., Leviant, I., Wing, K., Majewska, O., Bar, E., Malone, M., Poibeau, T., Reichart, R., & Korhonen, A. (2020). Multi-SimLex: A large-scale evaluation of multilingual and crosslingual lexical semantic similarity. Computational Linguistics, 46(4), 847\u2013897.","journal-title":"Computational Linguistics"},{"key":"9664_CR55","unstructured":"Wagner\u00a0Filho, J.\u00a0A., Wilkens, R., Idiart, M., & Villavicencio, A. (2018). The brWaC corpus: A new open resource for Brazilian Portuguese. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), pp. 4339\u20134344."},{"key":"9664_CR56","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1162\/tacl_a_00321","volume":"8","author":"A Warstadt","year":"2020","unstructured":"Warstadt, A., Parrish, A., Liu, H., Mohananey, A., Peng, W., Wang, S.-F., & Bowman, S. R. (2020). BLiMP: The benchmark of linguistic minimal pairs for English. Transactions of the Association for Computational Linguistics, 8, 377\u2013392.","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"9664_CR57","unstructured":"Wilkens, R., Zilio, L., Cordeiro, S.\u00a0R., Paula, F., Ramisch, C., Idiart, M., & Villavicencio, A. (2017). LexSubNC: A dataset of lexical substitution for nominal compounds. In IWCS 2017: 12th International Conference on Computational Semantics: Short papers."},{"key":"9664_CR58","first-page":"1","volume":"32","author":"Z Yang","year":"2019","unstructured":"Yang, Z., Dai, Z., Yang, Y., Carbonell, J., Salakhutdinov, R. R., & Le, Q. V. (2019). Xlnet: Generalized autoregressive pretraining for language understanding. Advances in Neural Information Processing Systems, 32, 1\u201310.","journal-title":"Advances in Neural Information Processing Systems"}],"container-title":["Language Resources and Evaluation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10579-023-09664-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10579-023-09664-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10579-023-09664-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,14]],"date-time":"2024-03-14T12:06:38Z","timestamp":1710417998000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10579-023-09664-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,2]]},"references-count":58,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,3]]}},"alternative-id":["9664"],"URL":"https:\/\/doi.org\/10.1007\/s10579-023-09664-1","relation":{},"ISSN":["1574-020X","1574-0218"],"issn-type":[{"type":"print","value":"1574-020X"},{"type":"electronic","value":"1574-0218"}],"subject":[],"published":{"date-parts":[[2023,6,2]]},"assertion":[{"value":"2 May 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 June 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}