{"id":"W4405990127","doi":"10.3917/arma.380.0016","title":"Université de Montréal : l’IA pour déchiffrer des documents manuscrits","year":2024,"lang":"fr","type":"article","venue":"Archimag.com.","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003628838,0.001141401,0.0008452494,0.00288386,0.005601849,0.01130563,0.001915545,0.00347808,0.2455384],"category_scores_gemma":[0.008781898,0.0007744118,0.0006757765,0.005429814,0.003141278,0.00430183,0.002785278,0.00407134,0.05022801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02605643,"about_ca_system_score_gemma":0.06705232,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8416163,"about_ca_topic_score_gemma":0.8496701,"domain_scores_codex":[0.9957072,0.0003908715,0.0001225797,0.0004862088,0.002449836,0.0008433263],"domain_scores_gemma":[0.9918142,0.0006840025,0.000342339,0.0007440514,0.003896298,0.002519162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007728294,0.00002420979,0.001022059,0.0002305326,0.00001305276,0.0002321171,0.0007547378,0.0001065223,0.001084571,0.02200364,0.8802546,0.0941967],"study_design_scores_gemma":[0.000007644145,0.000005180872,0.00268173,0.0000866683,0.000003054273,0.00006363748,0.0002896235,0.00004747695,0.0002699649,0.0003516372,0.9961811,0.00001227915],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00704199,0.1257016,0.004511739,0.18185,0.01536936,0.0002195506,0.01594451,0.003188846,0.6461724],"genre_scores_gemma":[0.03352258,0.020916,0.003456279,0.00367679,0.001035735,0.00008597103,0.002490078,0.0007975533,0.934019],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2455384,"threshold_uncertainty_score":0.8214077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02576556675640415,"score_gpt":0.226745102321484,"score_spread":0.2009795355650799,"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."}}