{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001141582,0.000164639,0.0004921493,0.0007269037,0.001281783,0.001229389,0.0004835597,0.0007533072,0.004412237],"category_scores_gemma":[0.006744044,0.000251853,0.0008008326,0.001112431,0.0003323326,0.0008219433,0.0008180572,0.001682609,0.0002446315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001042808,"about_ca_system_score_gemma":0.001471283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0141377,"about_ca_topic_score_gemma":0.02030356,"domain_scores_codex":[0.9989058,0.0002590005,0.00013081,0.00007253483,0.0001764947,0.000455348],"domain_scores_gemma":[0.9953791,0.001038701,0.001645562,0.00014011,0.0004496031,0.001347007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000120256,0.0002670758,0.9978822,0.000005794648,0.00002669186,0.00003109837,0.00008655209,0.00003802277,0.00003078655,0.00001865348,0.000180915,0.001311899],"study_design_scores_gemma":[0.00001224358,0.0001527675,0.9986565,0.00001523939,0.00001866811,0.00007034678,0.0005960217,0.0003157508,0.00002283464,0.00003519978,0.0001005764,0.000003849956],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989733,0.0001248403,0.00004248296,0.0001939215,0.000009235735,0.00001643422,0.0001701039,0.00000340781,0.0004662878],"genre_scores_gemma":[0.9992796,0.00006260102,0.00004547664,0.00009132594,0.00001732514,0.000008908322,0.0002799935,0.000002321635,0.0002126729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0141377,"threshold_uncertainty_score":0.0281108,"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."}}