{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004332797,0.0001569224,0.0003943867,0.0004639103,0.001096132,0.0001856058,0.00003925978,0.00008727687,0.00002220364],"category_scores_gemma":[0.001498868,0.000133761,0.00008601467,0.001560245,0.0002667927,0.00007314891,0.0001030948,0.0001559049,7.493637e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003535121,"about_ca_system_score_gemma":0.0001195026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000914098,"about_ca_topic_score_gemma":0.0003654255,"domain_scores_codex":[0.9987352,0.00002336179,0.0002913111,0.0005131802,0.0001100544,0.000326896],"domain_scores_gemma":[0.9989824,0.0002460488,0.0001046901,0.0002117804,0.0003805753,0.00007449637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001664866,0.001082192,0.8596481,0.0001755729,0.002139193,0.000109749,0.0036201,0.00002614085,0.02534387,0.005081551,0.0003996784,0.1023572],"study_design_scores_gemma":[0.01524274,0.000454643,0.2029786,0.0004948735,0.02614099,0.0004300598,0.1855177,0.4396382,0.09532019,0.02307711,0.00848532,0.002219555],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942813,0.0005642718,0.001550105,0.002984689,0.00001580911,0.0002110551,0.00005170247,0.00027246,0.00006859509],"genre_scores_gemma":[0.9184237,0.00001067309,0.08079533,0.00006899152,0.00001382742,0.00005320359,0.0003157698,0.00001178775,0.0003067971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6566696,"threshold_uncertainty_score":0.8430668,"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."}}