{"id":"W4415172472","doi":"10.1503/cmaj.250888-f","title":"Des innovations cruciales dans le domaine de la santé au Canada","year":2025,"lang":"fr","type":"article","venue":"Canadian Medical Association Journal","topic":"Health Sciences Research and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada); Vector Institute","funders":"","keywords":"Lien; MEDLINE; Drug industry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01620611,0.0005025635,0.00073025,0.002544386,0.01313939,0.01530421,0.00215889,0.008176289,0.01760747],"category_scores_gemma":[0.03137805,0.0004371033,0.0007117195,0.00484906,0.01574528,0.005655372,0.005067273,0.01270913,0.001223254],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1178477,"about_ca_system_score_gemma":0.4442253,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9434223,"about_ca_topic_score_gemma":0.9572602,"domain_scores_codex":[0.9801294,0.003965239,0.0006919751,0.001159748,0.008149506,0.005904133],"domain_scores_gemma":[0.9654609,0.00704897,0.00139205,0.0008297372,0.01180001,0.01346828],"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":[0.0002287663,0.0001803166,0.01524337,0.00175402,0.0001032421,0.001911125,0.02239051,0.001307187,0.00142043,0.3887282,0.2851674,0.2815655],"study_design_scores_gemma":[0.00004923395,0.0001036396,0.03102044,0.002924558,0.00006879692,0.0005219506,0.01881841,0.0008545115,0.0006128386,0.03666256,0.9082409,0.0001222617],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01266052,0.04310174,0.001343006,0.8900501,0.00407261,0.0000649007,0.0004344316,0.00005816435,0.04821462],"genre_scores_gemma":[0.6192433,0.1541801,0.007913171,0.1464303,0.005062389,0.0001463715,0.0007252987,0.0001551459,0.06614404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8821523,"threshold_uncertainty_score":0.8550487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02702382511409497,"score_gpt":0.4243585317455666,"score_spread":0.3973347066314717,"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."}}