{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007922775,0.0002271845,0.0001988342,0.0001878001,0.000187316,0.0003278452,0.0001359676,0.0002488702,0.0006813623],"category_scores_gemma":[0.00006827622,0.000110562,0.000341385,0.0001804489,0.0001999303,0.0003261378,0.0003435157,0.0005548497,0.0003560905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002687284,"about_ca_system_score_gemma":0.0002811784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007210119,"about_ca_topic_score_gemma":0.001097843,"domain_scores_codex":[0.9999208,0.000007104784,0.00000246911,0.0000165544,0.00003007487,0.00002292796],"domain_scores_gemma":[0.9999762,0.000005906019,0.000005170044,0.000003551825,0.000004597236,0.000004629931],"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":[0.0000258528,0.000006674987,0.00005313054,0.00002668862,0.000002627845,0.0000344599,0.000009511584,0.00006452813,0.9979133,0.0001135392,0.00003264138,0.001717082],"study_design_scores_gemma":[0.000003621888,0.00005025729,0.001494716,0.000003430773,0.000007115117,0.00007583807,0.00001928549,0.000816425,0.9947759,0.0001259668,0.002622091,0.000005298762],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758461,0.001279897,0.01793463,0.0002312023,0.00006146922,0.00002529297,0.0002755072,0.0001943806,0.004151601],"genre_scores_gemma":[0.9849356,0.0006492473,0.007385544,0.000105921,0.00001138125,0.00001929262,0.0002623976,0.00004307233,0.006587511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007210119,"threshold_uncertainty_score":0.002279401,"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."}}