{"id":"W7027967955","doi":"","title":"Drug reimbursement challenges (comparison between France and Quebec)","year":2013,"lang":"fr","type":"other","venue":"OpenGrey (Institut de l'Information Scientifique et Technique)","topic":"Telomeres, Telomerase, and Senescence","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Primary care; Abandonment (legal); Health insurance; Reimbursement","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":[0.003685564,0.0003380674,0.0005569904,0.002847685,0.001811799,0.006146702,0.0009148817,0.00159156,0.01302067],"category_scores_gemma":[0.01191267,0.0001956031,0.0009986582,0.004910664,0.0007850912,0.001362139,0.00123772,0.001077757,0.0007815702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07128485,"about_ca_system_score_gemma":0.04712768,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9649066,"about_ca_topic_score_gemma":0.9795123,"domain_scores_codex":[0.9956656,0.0008679062,0.0002265565,0.0002855031,0.001749778,0.00120464],"domain_scores_gemma":[0.9929159,0.001411867,0.00108462,0.0001489736,0.003245728,0.001193042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004669834,0.0007603863,0.4520887,0.001944244,0.001689014,0.001973837,0.003026356,0.01282749,0.001175238,0.05540555,0.1490173,0.3154221],"study_design_scores_gemma":[0.0003465609,0.0004915819,0.8783292,0.0009511671,0.000455823,0.0004881451,0.005273303,0.00354139,0.0003556419,0.0008324545,0.1088456,0.00008914369],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6831858,0.04008388,0.00118628,0.05846373,0.0007257656,0.0005550143,0.01408051,0.0001272636,0.2015919],"genre_scores_gemma":[0.9678295,0.0049681,0.0006159811,0.005336086,0.0001209866,0.00012526,0.002943687,0.00002310766,0.01803729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07128485,"threshold_uncertainty_score":0.5172102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0285521898350278,"score_gpt":0.2901141173527115,"score_spread":0.2615619275176837,"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."}}