{"id":"W4382724029","doi":"10.3390/pr11071953","title":"Optimization of Supercritical Carbon Dioxide Fluid Extraction of Medicinal Cannabis from Quebec","year":2023,"lang":"en","type":"article","venue":"Processes","topic":"Cannabis and Cannabinoid Research","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Collège de Maisonneuve; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cannabinol; Supercritical carbon dioxide; Supercritical fluid; Yield (engineering); Extraction (chemistry); Raw material; Box–Behnken design; Cannabis; Chromatography; Chemistry; Response surface methodology; Medicine; Materials science; Cannabidiol; Organic chemistry; Composite material","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":[0.000601983,0.0006016177,0.0004410594,0.0006458641,0.0006332045,0.0007979103,0.0004314939,0.0003467554,0.001578258],"category_scores_gemma":[0.0007963849,0.0001962275,0.0005318812,0.0007755259,0.0004065417,0.0003180699,0.0002685515,0.0003355231,0.0003650211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002396262,"about_ca_system_score_gemma":0.002720544,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2318375,"about_ca_topic_score_gemma":0.27957,"domain_scores_codex":[0.9996201,0.0000514158,0.00002290693,0.00006616959,0.0001722129,0.00006718795],"domain_scores_gemma":[0.9998185,0.00005357565,0.00002219119,0.000008272891,0.00008359086,0.00001392448],"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":[0.0009477576,0.0003189079,0.00285369,0.0005005234,0.00009344847,0.000221432,0.0001371012,0.02114335,0.9507275,0.0005825894,0.0004042852,0.02206945],"study_design_scores_gemma":[0.00007230401,0.0009776329,0.01733107,0.00003973129,0.0001225164,0.00008137503,0.0001765595,0.06331658,0.9103644,0.0001222276,0.007322762,0.00007284407],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856651,0.001219011,0.00744438,0.0001193014,0.00003149359,0.0002404991,0.0006452981,0.0001129737,0.004521966],"genre_scores_gemma":[0.985401,0.001278674,0.008905632,0.00004936888,0.000007967224,0.0001135884,0.0006291783,0.00003790229,0.003576751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7681625,"threshold_uncertainty_score":0.460976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01934167533224824,"score_gpt":0.3164998868468277,"score_spread":0.2971582115145795,"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."}}