{"id":"W4372202514","doi":"10.1016/j.josat.2023.209062","title":"Predictors of dropout from treatment among patients using specialized addiction treatment centers","year":2023,"lang":"en","type":"article","venue":"Journal of Substance Use and Addiction Treatment","topic":"Substance Abuse Treatment and Outcomes","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; McGill University; Douglas Mental Health University Institute","funders":"Health Canada; Institut Universitaire sur les Dépendances; Ministère de la Santé et des Services sociaux","keywords":"Medicine; Dropout (neural networks); Polysubstance dependence; Odds; Addiction; Odds ratio; Emergency department; Psychiatry; Logistic regression; Substance abuse; Emergency medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007457403,0.0004771015,0.001011943,0.0005355765,0.0001704628,0.0000421489,0.00005340587,0.0001440469,0.0001491317],"category_scores_gemma":[0.00001970217,0.00031756,0.0005234968,0.0004546715,0.0001263597,0.0005863234,0.000006680147,0.00007609134,0.00001036262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002065141,"about_ca_system_score_gemma":0.0001278288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004287935,"about_ca_topic_score_gemma":0.0004537245,"domain_scores_codex":[0.9977084,0.00008676254,0.000955904,0.0003584228,0.0005264599,0.0003640737],"domain_scores_gemma":[0.9980863,0.0001931426,0.0008318922,0.0003046217,0.0002670321,0.0003169596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002284062,0.0016424,0.9748004,0.000004665078,0.003435397,0.0002107997,0.004040347,0.00009143827,0.001132565,0.000003014836,0.0002836386,0.01207129],"study_design_scores_gemma":[0.02970953,0.006203243,0.940924,0.0005805733,0.003952181,0.00002658356,0.001237839,0.0003436896,0.01402407,0.00001613902,0.002732286,0.0002498525],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963503,0.001540094,0.0000281192,0.00005598199,0.00102006,0.0006993804,0.0001780386,0.00007925436,0.0000487682],"genre_scores_gemma":[0.9748877,0.0233031,0.0003598659,0.00001760411,0.0004522405,0.00002638276,0.0003051526,0.00005065895,0.0005972789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03387637,"threshold_uncertainty_score":0.9999276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04275650408464883,"score_gpt":0.2722468883948098,"score_spread":0.2294903843101609,"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."}}