{"id":"W4366426819","doi":"10.3390/molecules28083552","title":"Preventing Mislabeling: A Comparative Chromatographic Analysis for Classifying Medical and Industrial Cannabis","year":2023,"lang":"en","type":"article","venue":"Molecules","topic":"Cannabis and Cannabinoid Research","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Cannabis; Chromatography; Medicine; Chemistry; Psychiatry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.003419562,0.0007258668,0.0007141488,0.003858955,0.001076099,0.001293272,0.0009828776,0.001551805,0.001253818],"category_scores_gemma":[0.005029855,0.0003621731,0.0007929505,0.001556288,0.001306921,0.001054361,0.00103107,0.0007814681,0.0005974159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008273741,"about_ca_system_score_gemma":0.001151934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004537971,"about_ca_topic_score_gemma":0.006158701,"domain_scores_codex":[0.9969741,0.0005817077,0.0001438354,0.0006570077,0.00146283,0.0001805213],"domain_scores_gemma":[0.997738,0.0005241574,0.0002623567,0.0001867158,0.001161031,0.0001277029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001651947,0.0004880455,0.01657301,0.0006130771,0.000393021,0.0003267617,0.0004408293,0.0006192063,0.8538694,0.0007574171,0.0005334246,0.1237339],"study_design_scores_gemma":[0.0001870386,0.004440008,0.1611042,0.0002267012,0.001767557,0.007797441,0.0009387574,0.03397603,0.7667394,0.001182612,0.02114022,0.0005000655],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8945492,0.01358066,0.08344343,0.0005844253,0.0003388046,0.0007021088,0.0009788248,0.0009210167,0.004901647],"genre_scores_gemma":[0.8316254,0.005217456,0.1586063,0.0004476375,0.0001570634,0.0003132914,0.001211723,0.0001502095,0.002270933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004537971,"threshold_uncertainty_score":0.01808459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09063261732983889,"score_gpt":0.3701093939326465,"score_spread":0.2794767766028076,"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."}}