{"id":"W3116183120","doi":"10.1016/j.seppur.2020.118281","title":"Green extraction of perilla volatile organic compounds by pervaporation","year":2020,"lang":"en","type":"article","venue":"Separation and Purification Technology","topic":"Membrane Separation and Gas Transport","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Ministry of Science and Technology of the People's Republic of China","keywords":"Pervaporation; Chemistry; Permeation; Membrane; Perilla; Extraction (chemistry); Polydimethylsiloxane; Volatile organic compound; Chromatography; Chemical engineering; Organic chemistry","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":[0.00006125962,0.0001146969,0.0001594277,0.0001146665,0.00006046006,0.00001625088,0.0000754424,0.0001786412,0.0001958016],"category_scores_gemma":[0.00001128171,0.0001274694,0.00002256263,0.0004060931,0.0000621653,0.0001980299,0.000004453766,0.0001218059,0.00003832817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001500307,"about_ca_system_score_gemma":0.00001644797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004463511,"about_ca_topic_score_gemma":0.00001169392,"domain_scores_codex":[0.9992734,0.00001634008,0.0003323342,0.0001785089,0.0001058289,0.00009361205],"domain_scores_gemma":[0.9996291,0.00001094806,0.00008388246,0.0001398367,0.00007916077,0.00005708641],"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":[0.00001745226,0.00001845849,0.001000326,0.00007033911,0.00001755078,2.67869e-7,0.0005752214,0.0002638249,0.9862003,0.003157202,0.004946544,0.003732556],"study_design_scores_gemma":[0.0008049185,0.000222477,0.003535037,0.00001150634,0.00004282077,0.00001968545,0.0005110051,0.1279698,0.6773768,0.0007281681,0.1883887,0.0003890689],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9039207,0.001270926,0.0815283,0.00711584,0.0001635897,0.0004841689,0.00004358735,0.001035587,0.004437345],"genre_scores_gemma":[0.9986621,0.0002771126,0.0004661162,0.0001123088,0.00003285087,0.00001890807,0.0002514654,0.00001632371,0.0001627769],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3088235,"threshold_uncertainty_score":0.519805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01183487563566463,"score_gpt":0.2404530221356122,"score_spread":0.2286181464999476,"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."}}