{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007473179,0.0001237109,0.000411606,0.00007363277,0.0001076412,0.000006397471,0.0001291417,0.00002886293,0.00008292401],"category_scores_gemma":[0.000110378,0.0001082528,0.00003834003,0.0001997577,0.00001876467,0.00008834038,0.0004445275,0.0001344121,0.000001568137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007941677,"about_ca_system_score_gemma":0.0001499787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003314753,"about_ca_topic_score_gemma":0.00003825197,"domain_scores_codex":[0.9987589,0.0001095057,0.0004951174,0.0002031165,0.0003054247,0.0001279684],"domain_scores_gemma":[0.9991405,0.00007110395,0.0004464723,0.0002090272,0.00007159244,0.00006127579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003778172,0.0001549509,0.5422016,0.00007909282,0.0001441482,0.000001495304,0.007408379,0.4465712,0.0001535995,0.0002804161,0.00003729212,0.002590015],"study_design_scores_gemma":[0.004181971,0.0005418423,0.7005123,0.0002366328,0.0003349331,0.0000031621,0.001459749,0.2879174,0.003965872,0.0003477503,0.0003232999,0.0001751466],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967807,0.00009640442,0.00141055,0.0002340588,0.0000447189,0.001038473,0.00002949229,0.00001195918,0.00035365],"genre_scores_gemma":[0.9314321,0.00002272071,0.0679311,0.00004441043,0.00000709924,0.00009878228,0.0001907995,0.00001903265,0.0002539888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1586538,"threshold_uncertainty_score":0.4414419,"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."}}