{"id":"W7084107898","doi":"10.64628/aap.kxqxfxpe7","title":"Handicap et intelligence artificielle se nourrissent-ils mutuellement ?","year":2025,"lang":"fr","type":"article","venue":"","topic":"Media, Gender, and Advertising","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Context (archaeology); Subject (documents); Interpretation (philosophy)","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001558986,0.0002335884,0.0002719898,0.0001288149,0.0006804585,0.0001801673,0.0003963393,0.0001841881,0.01157148],"category_scores_gemma":[0.0002571959,0.0002295942,0.0001609,0.0008095036,0.0005942736,0.0002155883,0.0001640507,0.0002811385,0.001131155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002537624,"about_ca_system_score_gemma":0.0007028777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005530696,"about_ca_topic_score_gemma":0.003297286,"domain_scores_codex":[0.9971756,0.0003916705,0.0005293861,0.0004948017,0.0005217348,0.0008867634],"domain_scores_gemma":[0.9987593,0.0003852153,0.0001075706,0.0003188733,0.00009874992,0.0003302413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001685512,0.0005424557,0.0006784953,0.000182671,0.0001160014,0.00003656476,0.06742706,0.0006014832,0.0006436416,0.5412348,0.1251704,0.2633496],"study_design_scores_gemma":[0.000158782,0.00006637559,0.00007657998,0.0003439293,0.00007131464,0.000001357983,0.1079839,0.004978311,0.01022072,0.01341275,0.8623558,0.000330179],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0201277,0.01110833,0.1247042,0.07221498,0.008775827,0.0005579471,0.00001331338,0.0001281727,0.7623695],"genre_scores_gemma":[0.4007594,0.003341942,0.001364331,0.004211655,0.000465145,0.00001259437,0.000007609974,0.0000123339,0.589825],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7371854,"threshold_uncertainty_score":0.9996466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.066312361208124,"score_gpt":0.3934947712802577,"score_spread":0.3271824100721337,"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."}}