{"id":"W3135216460","doi":"10.1002/dta.3022","title":"Implementing an integrated multi‐technology platform for drug checking: Social, scientific, and technological considerations","year":2021,"lang":"en","type":"article","venue":"Drug Testing and Analysis","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Vancouver Foundation; Western Canada Research Grid; IBM Canada; Compute Canada; University of Victoria; Health Canada; Health Research; Agilent Technologies","keywords":"Harm reduction; SAFER; Computer science; Illicit drug; Service (business); Data science; Computer security; Medicine; Drug; Business; Public health; Psychiatry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.04192022,0.0008380137,0.0004650421,0.001486498,0.003583357,0.012895,0.004255932,0.005677182,0.005449675],"category_scores_gemma":[0.02909652,0.0005685336,0.0009827412,0.00109104,0.003760582,0.01230555,0.009052223,0.005040809,0.001760238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002695411,"about_ca_system_score_gemma":0.02067193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006896702,"about_ca_topic_score_gemma":0.01072814,"domain_scores_codex":[0.969238,0.0165463,0.00142788,0.001464685,0.008469418,0.002853617],"domain_scores_gemma":[0.9595438,0.01714542,0.002526905,0.004783247,0.010615,0.005385715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004816389,0.002778564,0.03668081,0.002874326,0.0002724815,0.002010287,0.01094551,0.005585802,0.02108571,0.1302754,0.05683988,0.7301696],"study_design_scores_gemma":[0.0002602861,0.004391099,0.03497871,0.005580798,0.0003346394,0.004190563,0.03441535,0.02829472,0.02673949,0.1226281,0.7376645,0.0005217728],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1248948,0.01071364,0.2460922,0.5412588,0.002613253,0.002459158,0.0004858435,0.002202812,0.06927956],"genre_scores_gemma":[0.3610111,0.007173963,0.592258,0.02592385,0.001156839,0.00160477,0.0004473589,0.0004187891,0.01000531],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04192022,"threshold_uncertainty_score":0.2216979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05798837842935545,"score_gpt":0.333504440895127,"score_spread":0.2755160624657715,"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."}}