{"id":"W2981413121","doi":"10.1016/j.sopen.2019.09.002","title":"Removing abuse-prone prescription medication from fueling the national opioid crisis through community engagement and surgeon leadership: results of a local drug take-back event","year":2019,"lang":"en","type":"article","venue":"Surgery Open Science","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Covenant Health","funders":"University of Michigan","keywords":"Hydrocodone; Medicine; Medical prescription; Dispose pattern; Prescription Drug Misuse; Substance abuse; Medical emergency; Family medicine; Opioid; Psychiatry; Oxycodone; Nursing; Opioid use disorder","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.008301718,0.0001602745,0.0003429636,0.0001240602,0.000438749,0.0001121508,0.000584115,0.00004756332,0.0001058095],"category_scores_gemma":[0.0006952381,0.0001170747,0.00006487899,0.0005413924,0.0004839472,0.0007050865,0.0003575867,0.0003258743,0.00004344944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002587812,"about_ca_system_score_gemma":0.0006491499,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01028937,"about_ca_topic_score_gemma":0.0002538307,"domain_scores_codex":[0.9969156,0.0005115725,0.0005800406,0.0004579936,0.001237435,0.0002973584],"domain_scores_gemma":[0.9973243,0.00123066,0.0003279499,0.0006728118,0.0003488162,0.00009542038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.005159136,0.00600094,0.3208736,0.002165794,0.0007944438,0.00001954793,0.427838,0.001857044,0.06729468,0.001348741,0.08345875,0.0831893],"study_design_scores_gemma":[0.004034033,0.0002273242,0.7951124,0.002235302,0.0001847599,0.00001596434,0.145552,0.005625057,0.03634396,0.001631967,0.008503806,0.0005333445],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908331,0.0005802186,0.0003742191,0.005433101,0.0003742399,0.001108571,0.00004402501,0.00002046098,0.001232032],"genre_scores_gemma":[0.9974289,0.0002746744,0.001032349,0.0007911085,0.00003148195,0.00003854035,0.0001209407,0.00001246261,0.0002695754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4742388,"threshold_uncertainty_score":0.9963012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1338137729317101,"score_gpt":0.3338451080737845,"score_spread":0.2000313351420744,"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."}}