{"id":"W4411850524","doi":"10.1007/978-3-031-92534-4_3","title":"The Future of Text-Matching Software: From Detecting Artificial Intelligence to Preventing Plagiarism","year":2025,"lang":"en","type":"book-chapter","venue":"","topic":"Academic integrity and plagiarism","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Matching (statistics); Plagiarism detection; Computer science; Software; Artificial intelligence; Natural language processing; Software engineering; Programming language; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.002839567,0.000302562,0.0004194602,0.0001229083,0.001547075,0.0001720606,0.001091415,0.00239866,0.0006295728],"category_scores_gemma":[0.001358655,0.0002397478,0.0002525196,0.0001208935,0.0002620946,0.0001232354,0.000313434,0.004050243,0.000107911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001446406,"about_ca_system_score_gemma":0.0004649046,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005618839,"about_ca_topic_score_gemma":0.01853003,"domain_scores_codex":[0.9973454,0.0001701236,0.0008012988,0.000467572,0.0007667739,0.0004488704],"domain_scores_gemma":[0.9958888,0.002987732,0.0004467313,0.0003211198,0.0002344173,0.0001211893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001377134,0.000002986323,0.000004048238,0.00001141593,0.00004751523,0.000001586788,0.006783862,0.000008494592,0.00001138969,0.5482724,0.001430256,0.4434123],"study_design_scores_gemma":[0.0000078899,0.00001091949,0.000001335405,0.0004106927,0.00004994593,2.885832e-7,0.008542315,0.00001985628,0.000370195,0.6198642,0.370489,0.0002333768],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003212987,0.002730906,0.1771619,0.007887338,0.004481899,0.0009835679,0.000104042,0.000260468,0.8060686],"genre_scores_gemma":[0.01522409,0.001872829,0.02742428,0.001456081,0.008227686,0.00002591884,0.00003275043,0.00007938625,0.945657],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.443179,"threshold_uncertainty_score":0.9997528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02183207765520005,"score_gpt":0.291037073097101,"score_spread":0.2692049954419009,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}