{"id":"W6902070478","doi":"10.6084/m9.figshare.26569573","title":"Additional file 3 of Legal sourcing of ten cannabis products in the Canadian cannabis market, 2019–2021: a repeat cross-sectional study","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Cannabis and Cannabinoid Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Multinomial logistic regression; Cannabis; Logistic regression; Legislation; Regression analysis","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009500926,0.0006742111,0.0009027485,0.002794217,0.002676477,0.00117483,0.001890463,0.0008148887,0.5230682],"category_scores_gemma":[0.01451303,0.0004685554,0.0009768612,0.005383812,0.0003472278,0.001190362,0.0009464879,0.000907369,0.03059359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006399175,"about_ca_system_score_gemma":0.01111253,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8384423,"about_ca_topic_score_gemma":0.8748879,"domain_scores_codex":[0.9991453,0.00007284973,0.000123805,0.0001389306,0.0003067167,0.0002124796],"domain_scores_gemma":[0.9910673,0.002306165,0.001097726,0.0005483938,0.004550428,0.0004299284],"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":[0.0002590996,0.0001352786,0.02937608,0.001091597,0.0000777299,0.00007676989,0.0002342463,0.0002496132,0.00005564835,0.0007090139,0.9610261,0.006708668],"study_design_scores_gemma":[0.002255858,0.0002219871,0.5947331,0.003319337,0.0003430746,0.0003651289,0.003289117,0.001660655,0.000481071,0.001785261,0.3913272,0.0002183272],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.001609709,0.00002438654,0.00005776548,0.00009699228,0.00001116244,0.0001409243,0.996183,0.00002979655,0.001846288],"genre_scores_gemma":[0.04262587,0.0002442879,0.001481863,0.000462947,0.00005089225,0.002993111,0.926312,0.0001262166,0.02570279],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5230682,"threshold_uncertainty_score":0.6802852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02335247726913352,"score_gpt":0.2955152323942666,"score_spread":0.2721627551251331,"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."}}