CCASL: Counterexamples to Comparative Analysis of Scientific Literature - Application to Polymers

CCASL: Counterexamples to Comparative Analysis of Scientific Literature - Application to Polymers | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article CCASL: Counterexamples to Comparative Analysis of Scientific Literature - Application to Polymers Aymar TCHAGOUE, Véronique EGLIN, Sébastien PRUVOST, Jean-Marc PETIT, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6074889/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Feb, 2026 Read the published version in Data & Knowledge Engineering → Version 1 posted You are reading this latest preprint version Abstract The exponential growth of scientific publications has made the exploration and comparative analysis of scientific literature increasingly complex and difficult.For instance, eliciting two scientific publications that diverge on widely accepted concepts within their domain turns out to be more and more difficult despite its great interest.We are interested in the automatic detection of these discrepancies using the latest artificial intelligence (AI) techniques. Given a particular scientific domain, we focus on large-scale analysis of the tables present in related scientific publications and propose to capture domain knowledge with arbitrary functions.In this setting, we propose a five-step method, called CCASL: (1) Modeling the domain knowledge with functions expressed as approximate functional dependencies (FDs), (2) Acquiring a corpus of scientific documents related to the proposed functions, (3) Analysing all tables occurring in the PDF documents and producing a consolidated table from them, (4) Detecting counterexamples of the FDs in the consolidated table, and (5) Conducting a comparative analysis of the pairs of papers containing the detected counterexamples. We have applied CCASL to a subfield of polymer research, known as Epoxy-Amine networks (EA). In collaboration with material scientists, we have identified an intuitive function \(f_{EA}\) that relates the storage modulus \((SM)\) , the structure of the polymer \((V_{EA})\) , and its glass transition temperature \((T_g)\) . Based on this function, we have implemented all the 5 steps of CCASL. First results show that CCASL is proving to be a powerful approach for bibliographic confrontation in the field of polymers. functional dependency comparative analysis tables analysis machine learning counterexample polymers Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 03 Feb, 2026 Read the published version in Data & Knowledge Engineering → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6074889","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":420962245,"identity":"b0e1164e-9c4f-4f09-912b-4f3320f6b773","order_by":0,"name":"Aymar TCHAGOUE","email":"data:image/png;base64,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","orcid":"","institution":"LIRIS UMR-5205","correspondingAuthor":true,"prefix":"","firstName":"Aymar","middleName":"","lastName":"TCHAGOUE","suffix":""},{"id":420962247,"identity":"e91c9965-73ea-4be4-8e5b-b3ff46659046","order_by":1,"name":"Véronique EGLIN","email":"","orcid":"","institution":"LIRIS UMR-5205","correspondingAuthor":false,"prefix":"","firstName":"Véronique","middleName":"","lastName":"EGLIN","suffix":""},{"id":420962248,"identity":"7164c39f-882c-4ee7-b491-a287f2d8de91","order_by":2,"name":"Sébastien PRUVOST","email":"","orcid":"","institution":"IMP UMR-5223","correspondingAuthor":false,"prefix":"","firstName":"Sébastien","middleName":"","lastName":"PRUVOST","suffix":""},{"id":420962249,"identity":"d18ddb70-2d7c-49e7-b0a6-bb206ccd684a","order_by":3,"name":"Jean-Marc PETIT","email":"","orcid":"","institution":"LIRIS UMR-5205","correspondingAuthor":false,"prefix":"","firstName":"Jean-Marc","middleName":"","lastName":"PETIT","suffix":""},{"id":420962250,"identity":"8ae6d819-80ec-4707-ad84-f8c27649789e","order_by":4,"name":"Jannick DUCHET-RUMEAU","email":"","orcid":"","institution":"IMP UMR-5223","correspondingAuthor":false,"prefix":"","firstName":"Jannick","middleName":"","lastName":"DUCHET-RUMEAU","suffix":""},{"id":420962251,"identity":"c3c3dbdf-a432-4125-8754-abc508ae3672","order_by":5,"name":"Jean-Francois GERARD","email":"","orcid":"","institution":"IMP UMR-5223","correspondingAuthor":false,"prefix":"","firstName":"Jean-Francois","middleName":"","lastName":"GERARD","suffix":""}],"badges":[],"createdAt":"2025-02-20 22:38:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6074889/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6074889/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1016/j.datak.2026.102574","type":"published","date":"2026-02-04T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":101974133,"identity":"07f17f0e-4c2b-46f1-8394-b1411cb45cb1","added_by":"auto","created_at":"2026-02-05 15:17:07","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":988392,"visible":true,"origin":"","legend":"","description":"","filename":"CCASLTechnicalCheck.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6074889/v1_covered_57de4552-b669-485c-a0e5-152f5c81c9ea.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"CCASL: Counterexamples to Comparative Analysis of Scientific Literature - 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Given a particular scientific domain, we focus on large-scale analysis of the tables present in related scientific publications and propose to capture domain knowledge with arbitrary functions.In this setting, we propose a five-step method, called CCASL: (1) Modeling the domain knowledge with functions expressed as approximate functional dependencies (FDs), (2) Acquiring a corpus of scientific documents related to the proposed functions, (3) Analysing all tables occurring in the PDF documents and producing a consolidated table from them, (4) Detecting counterexamples of the FDs in the consolidated table, and (5) Conducting a comparative analysis of the pairs of papers containing the detected counterexamples. We have applied CCASL to a subfield of polymer research, known as Epoxy-Amine networks (EA). 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