{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006391905,0.0001448465,0.0004487308,0.000640785,0.000184221,0.0000545126,0.00009543633,0.0001700681,0.00008510179],"category_scores_gemma":[0.0004516054,0.0001239139,0.0002389135,0.001839587,0.0001622249,0.00003239424,0.00009442398,0.0002608939,0.000004840866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002980615,"about_ca_system_score_gemma":0.0002470242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001528968,"about_ca_topic_score_gemma":0.0002152457,"domain_scores_codex":[0.9982945,0.00006746181,0.0002902009,0.0003583111,0.0005754257,0.000414107],"domain_scores_gemma":[0.9992641,0.00003776814,0.00006441785,0.0001791477,0.0001450453,0.0003094813],"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":[0.001154334,0.0006297134,0.2705866,0.001395217,0.009093726,0.0008629246,0.00458103,0.0002070166,0.03499781,0.001582203,0.6267471,0.0481623],"study_design_scores_gemma":[0.01971214,0.002069877,0.3894061,0.001098906,0.005094925,0.0002327229,0.006906014,0.2548972,0.01922785,0.0008595224,0.2989739,0.001520838],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802123,0.0005219193,0.0005641265,0.01763216,0.0000620693,0.000570072,0.00002534168,0.000107301,0.0003047622],"genre_scores_gemma":[0.9942358,0.00007537488,0.0001982281,0.0002098786,0.0001998761,0.0002438885,0.0001272942,0.00002318737,0.004686455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3277732,"threshold_uncertainty_score":0.5053062,"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."}}