{"id":"W7011309551","doi":"","title":"L’histoire nous le dira ; Tabarnouche, pâté chinois et autres traits culturels du Québec","year":2024,"lang":"fr","type":"article","venue":"Érudit (Université de Montréal)","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gender relations; Immigration; Context (archaeology)","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":[0.001754549,0.0004833466,0.0002805071,0.001977264,0.01064149,0.004950273,0.001129875,0.00133082,0.01370434],"category_scores_gemma":[0.003562252,0.0002333124,0.0002827435,0.003445837,0.007700772,0.002019423,0.001365443,0.002672429,0.0008525521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04390523,"about_ca_system_score_gemma":0.04082162,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9788383,"about_ca_topic_score_gemma":0.9894818,"domain_scores_codex":[0.9986956,0.0003357463,0.00003857348,0.0001490506,0.0004666699,0.0003144077],"domain_scores_gemma":[0.9977676,0.0003411712,0.0001452414,0.00008901179,0.001374273,0.0002827076],"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":[0.0001015631,0.00004675447,0.0440536,0.0007605473,0.00007953864,0.001366535,0.1640708,0.0005747623,0.002345384,0.1702702,0.4872949,0.1290353],"study_design_scores_gemma":[0.000004311692,0.00001319866,0.05494076,0.0007661218,0.00002525482,0.0003168488,0.09695084,0.0002179106,0.000625727,0.004786369,0.8412779,0.00007476573],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.135598,0.07115033,0.008726297,0.3473329,0.009043287,0.0003509613,0.004412107,0.0001600418,0.423226],"genre_scores_gemma":[0.6267663,0.02781012,0.003226753,0.01736753,0.0004518853,0.0002159616,0.0007693975,0.0001445107,0.3232476],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04390523,"threshold_uncertainty_score":0.3185562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01752853540412515,"score_gpt":0.2449982790508932,"score_spread":0.227469743646768,"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."}}