{"id":"W2592358551","doi":"10.1016/j.respe.2017.01.089","title":"Capacité du PMSI-MCO à identifier la fragilité des personnes âgées","year":2017,"lang":"fr","type":"article","venue":"Revue d Épidémiologie et de Santé Publique","topic":"Health, Medicine and Society","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004349883,0.0008687981,0.0009829679,0.002012934,0.0005327881,0.001892002,0.001309027,0.001683644,0.006483006],"category_scores_gemma":[0.02818349,0.0003593616,0.001601761,0.0009888875,0.0003084798,0.001121747,0.001358303,0.000955956,0.00254081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000857991,"about_ca_system_score_gemma":0.001193323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01840467,"about_ca_topic_score_gemma":0.01442827,"domain_scores_codex":[0.9970021,0.001203048,0.0002482459,0.0004610055,0.0007262324,0.0003594576],"domain_scores_gemma":[0.9887173,0.005659464,0.001880235,0.0005082485,0.002419702,0.0008148924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003271953,0.0001679099,0.9716113,0.0001154669,0.0001692987,0.00004306295,0.0002771978,0.000315972,0.0001886012,0.0001245306,0.002048038,0.0246115],"study_design_scores_gemma":[0.00003791065,0.0007473505,0.9797658,0.0002536147,0.0003862062,0.000609947,0.001168891,0.008043999,0.0008471717,0.0005937681,0.00749197,0.00005324222],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9635037,0.004024275,0.004464331,0.002780262,0.0004960317,0.000452173,0.01080368,0.0003175963,0.01315785],"genre_scores_gemma":[0.9844014,0.001039741,0.004950492,0.000412421,0.000266454,0.0003340189,0.003483186,0.00003415087,0.00507808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01840467,"threshold_uncertainty_score":0.03659505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08284632351955028,"score_gpt":0.4232745588802787,"score_spread":0.3404282353607284,"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."}}