{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005684252,0.0005333287,0.0006535603,0.0001973941,0.0008894443,0.0001509194,0.0003359681,0.001027257,0.0003950941],"category_scores_gemma":[0.003061798,0.0005694324,0.000183354,0.0005477166,0.0004847104,0.001117433,0.0000974582,0.00145336,0.000594328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003039496,"about_ca_system_score_gemma":0.001127483,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03290426,"about_ca_topic_score_gemma":0.02072207,"domain_scores_codex":[0.9896463,0.006422034,0.001109302,0.0006595689,0.0006101084,0.001552641],"domain_scores_gemma":[0.9946304,0.003258641,0.0005684874,0.0004907834,0.000506779,0.0005449195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007056816,0.001403832,0.368764,0.008976981,0.0003056756,0.0003733023,0.03737019,0.2055348,0.0005273181,0.1643978,0.1382156,0.07342482],"study_design_scores_gemma":[0.001232188,0.0003045888,0.8597561,0.008061992,0.0001070219,0.00009351836,0.001511551,0.0006858243,0.000345678,0.04539899,0.08197608,0.0005265145],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7680814,0.0459864,0.005491225,0.1385485,0.002962681,0.001520898,0.0003040156,0.0006679341,0.03643704],"genre_scores_gemma":[0.9271505,0.03528704,0.02975096,0.004330259,0.0005298979,0.0002026184,0.0001125995,0.00008973858,0.002546355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.490992,"threshold_uncertainty_score":0.9996757,"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."}}