{"id":"W4390034104","doi":"10.7202/1092741ar","title":"VIEILLISSEMENT DE LA POPULATION ET DÉPENSES DE L’ASSURANCE MALADIE","year":2004,"lang":"fr","type":"article","venue":"Assurances et gestion des risques","topic":"Global Health Care Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001350058,0.0002064093,0.0002592035,0.00165385,0.0004513848,0.0005674711,0.0003076533,0.0006360345,0.006259581],"category_scores_gemma":[0.009820235,0.0001240066,0.0003551751,0.001671265,0.0003253589,0.0007345806,0.0005580912,0.0009657283,0.0006130221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008734234,"about_ca_system_score_gemma":0.0007959247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04740018,"about_ca_topic_score_gemma":0.04648228,"domain_scores_codex":[0.9988374,0.0003565421,0.0001090727,0.00009765761,0.0004642591,0.0001350511],"domain_scores_gemma":[0.9963108,0.0009407231,0.001326888,0.0001367906,0.0009248847,0.0003599402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002154659,0.0001520968,0.7728546,0.0003583899,0.0001617389,0.0003594472,0.003331923,0.0006510427,0.0006484536,0.003301864,0.0260588,0.1919061],"study_design_scores_gemma":[0.000002763488,0.00009921005,0.9790044,0.0001520135,0.00001487102,0.000500081,0.0006577304,0.0001674757,0.0001244783,0.0005179451,0.0187382,0.00002084917],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8158176,0.0557328,0.002674125,0.0347577,0.001030818,0.00008730468,0.02746794,0.0001832008,0.06224855],"genre_scores_gemma":[0.9635209,0.01521723,0.001475796,0.0008992597,0.0006218742,0.0001019431,0.006287206,0.00002853297,0.01184733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04740018,"threshold_uncertainty_score":0.09424853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04759825522840561,"score_gpt":0.4300473349917435,"score_spread":0.3824490797633379,"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."}}