{"id":"W220950506","doi":"","title":"The programme for decentralized training and the retention of general practitioners in the Bas-Saint-Laurent region of Québec.","year":2009,"lang":"en","type":"article","venue":"Canadian Family Physician","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"SAINT; Training (meteorology); Computer science; Computer network; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001540202,0.0002035857,0.0001603304,0.0004378564,0.002868267,0.0007749722,0.001021826,0.001014868,0.01226769],"category_scores_gemma":[0.003512702,0.0002006669,0.0002519702,0.0006054023,0.0008948237,0.0005073988,0.00176595,0.001139657,0.0006673568],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02635472,"about_ca_system_score_gemma":0.115176,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9636941,"about_ca_topic_score_gemma":0.9873581,"domain_scores_codex":[0.9990024,0.0002201034,0.00001232992,0.00006498797,0.0001174101,0.0005827003],"domain_scores_gemma":[0.99366,0.000285933,0.0002512491,0.0001524735,0.0007689877,0.004881289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001310361,0.002005909,0.422442,0.0006541944,0.0000818366,0.0009057976,0.005711263,0.001874164,0.004847708,0.01187271,0.2367934,0.3115007],"study_design_scores_gemma":[0.0002788993,0.0002939152,0.9421138,0.0002026462,0.00001322311,0.00009031198,0.001992328,0.0005159687,0.000142598,0.0002393964,0.05409434,0.00002240577],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8834857,0.002813897,0.001478919,0.04374291,0.0008354529,0.001465654,0.005477545,0.0002594466,0.06044032],"genre_scores_gemma":[0.9124466,0.0008294188,0.00262975,0.005534497,0.0001892598,0.0006862913,0.001769516,0.00002773764,0.07588693],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9736453,"threshold_uncertainty_score":0.1912178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08086406166822648,"score_gpt":0.3565679047936856,"score_spread":0.2757038431254591,"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."}}