{"id":"W4384297789","doi":"10.2196/preprints.50858","title":"Identifying Shared Opioid Supplies from Public Data on Opioid Deaths (Preprint)","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Opioid; Opioid overdose; Public health; Law enforcement; Fentanyl; Business; Enforcement; Medicine; Environmental health; Political science; (+)-Naloxone; Anesthesia; Nursing; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080036,0.0002134288,0.0002285699,0.003948335,0.0003938995,0.001267348,0.000338567,0.0003147583,0.01782371],"category_scores_gemma":[0.005844345,0.0001439434,0.0002105931,0.006612557,0.0002140489,0.0003804778,0.0009267962,0.000238591,0.006683566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009567095,"about_ca_system_score_gemma":0.002173791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0853387,"about_ca_topic_score_gemma":0.1246954,"domain_scores_codex":[0.9991443,0.00009318875,0.00006881709,0.00009431295,0.0004949296,0.0001044233],"domain_scores_gemma":[0.9958315,0.001670335,0.0008510793,0.0004785121,0.001048413,0.0001201394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003467461,0.0001339178,0.3530835,0.0006430544,0.0001214252,0.0005978587,0.001223176,0.00422896,0.002436842,0.003582099,0.499956,0.1336465],"study_design_scores_gemma":[0.00003667667,0.00005150218,0.7725115,0.0001725256,0.00003689829,0.0003531518,0.00277064,0.005538913,0.002810506,0.001293118,0.2143897,0.00003473392],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1596567,0.0003069176,0.004093428,0.001209229,0.0003081046,0.0002077011,0.8024578,0.001672362,0.03008783],"genre_scores_gemma":[0.2736678,0.0004300442,0.008334093,0.000133988,0.0001904025,0.0001711254,0.6996927,0.0003345684,0.01704523],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0853387,"threshold_uncertainty_score":0.169684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1503030730671392,"score_gpt":0.3585024124439002,"score_spread":0.208199339376761,"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."}}