{"id":"W4313257242","doi":"10.1001/jamanetworkopen.2022.48559","title":"Development and Validation of a Machine Learning Model to Estimate Risk of Adverse Outcomes Within 30 Days of Opioid Dispensation","year":2022,"lang":"en","type":"article","venue":"JAMA Network Open","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"College of Physicians and Surgeons of Ontario; University of Alberta","funders":"","keywords":"Medicine; Adverse effect; Psychological intervention; Emergency medicine; Pharmacy; Population; Opioid; Medical prescription; Medical emergency; Family medicine; Internal medicine; Psychiatry; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.005740566,0.001088126,0.0006723093,0.001139728,0.0005377774,0.001089688,0.001282395,0.001055912,0.001199276],"category_scores_gemma":[0.01035717,0.0003676432,0.0008124104,0.0005753979,0.0004635243,0.0006147721,0.0007356135,0.001459497,0.0004097887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002006372,"about_ca_system_score_gemma":0.004096697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.069391,"about_ca_topic_score_gemma":0.03994337,"domain_scores_codex":[0.9990246,0.0003744176,0.00007972319,0.0002126726,0.0001920868,0.0001164573],"domain_scores_gemma":[0.9950475,0.00297109,0.000445928,0.0001728679,0.001232608,0.0001301395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002066939,0.0003445749,0.1766288,0.00007429197,0.000208545,0.0001402727,0.00009299711,0.768114,0.0008766771,0.000852161,0.001897111,0.05056385],"study_design_scores_gemma":[0.00001405629,0.0000916519,0.008578509,0.00002180019,0.00002022617,0.00002247334,0.00002572,0.9901339,0.0003488786,0.0004569551,0.0002779432,0.000007824013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.745434,0.0005498176,0.2460238,0.001682167,0.0001221394,0.0005293291,0.001808815,0.000875973,0.002973856],"genre_scores_gemma":[0.9566915,0.0001412669,0.0404477,0.0001691898,0.00002948856,0.0002059074,0.001133257,0.00002028723,0.00116132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.069391,"threshold_uncertainty_score":0.1379742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02467990382482479,"score_gpt":0.30579346173583,"score_spread":0.2811135579110052,"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."}}