{"id":"W2890969745","doi":"10.1111/add.14408","title":"Commentary on Liang <i>et al</i>. (2018): The potential impact of medical cannabis on public health with respect to reducing prescription opioid use and associated harm","year":2018,"lang":"en","type":"letter","venue":"Addiction","topic":"Cannabis and Cannabinoid Research","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mental Health Research Canada; Public Health Ontario; University of Toronto","funders":"Institute of Neurosciences, Mental Health and Addiction; Canadian Institutes of Health Research","keywords":"Medical prescription; Medicine; Codeine; Medicaid; Cannabis; Psychiatry; Public health; Opioid; Prescription Drug Misuse; Pharmacology; Health care; Opioid use disorder; Internal medicine; Morphine","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":[0.009109564,0.001786112,0.00318876,0.001777911,0.005017597,0.006275339,0.009436344,0.06660508,0.01988683],"category_scores_gemma":[0.05741468,0.001276447,0.002883045,0.00216777,0.00546544,0.006015693,0.003363676,0.05990932,0.0162587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007100569,"about_ca_system_score_gemma":0.01340121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03317839,"about_ca_topic_score_gemma":0.02951103,"domain_scores_codex":[0.9933937,0.002022938,0.0007821055,0.0009377943,0.002049078,0.0008144293],"domain_scores_gemma":[0.9647655,0.02050122,0.001990655,0.0009590197,0.009005317,0.002778211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001865173,0.000006296642,0.00005200927,0.0001151566,0.000008356848,0.00003894248,0.00004820293,0.00001058168,0.00001671556,0.0003785769,0.9977247,0.001581865],"study_design_scores_gemma":[0.000127929,0.00004803412,0.0007305378,0.002181136,0.00006744773,0.0002329559,0.0005361244,0.000136287,0.0001564747,0.005042356,0.9906501,0.00009061665],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00007452156,0.002657132,0.00005336442,0.9233323,0.07254226,0.00002258885,0.0003429055,0.00003897186,0.0009358756],"genre_scores_gemma":[0.0006052677,0.001643573,0.00007778972,0.943393,0.05206204,0.00005475749,0.00006266157,0.00002833046,0.002072679],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.06660508,"threshold_uncertainty_score":0.06652802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03274972101510892,"score_gpt":0.326452392324206,"score_spread":0.2937026713090971,"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."}}