{"id":"W4404447360","doi":"10.1016/j.jece.2024.114765","title":"Prediction of fixed-bed GAC filter consumption for complex VOC mixtures using a parsimonious competitive adsorption model and a single batch test","year":2024,"lang":"en","type":"article","venue":"Journal of environmental chemical engineering","topic":"Odor and Emission Control Technologies","field":"Chemical Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Adsorption; Filter (signal processing); Consumption (sociology); Process engineering; Chemistry; Environmental science; Chromatography; Materials science; Chemical engineering; Computer science; 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":[0.00009551619,0.0001702548,0.0002897587,0.000110796,0.00001744806,0.00002149542,0.00008683583,0.0001487273,0.00002809673],"category_scores_gemma":[0.0001380275,0.0001560618,0.0001324727,0.00004965686,0.00006072399,0.0001670366,0.00005121312,0.0002605282,5.851456e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001916386,"about_ca_system_score_gemma":0.000006828454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.148136e-7,"about_ca_topic_score_gemma":3.178783e-8,"domain_scores_codex":[0.9990529,0.000003858969,0.0004268268,0.0001545829,0.0001836414,0.0001781867],"domain_scores_gemma":[0.999478,0.0002511946,0.00009861738,0.00007840282,0.00001454926,0.00007921442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004224146,0.00006932567,0.0001659671,0.0002235965,0.00005753749,0.000003120306,0.00006258309,0.03650411,0.9621958,0.00003990617,0.00005046181,0.0005853099],"study_design_scores_gemma":[0.0003834284,0.00006328927,0.0001055917,0.0002464057,0.00005964525,0.00005165866,0.00002363804,0.5770768,0.4217788,0.00004747256,0.00007966995,0.00008356557],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9087164,0.0009930762,0.08974893,0.00005218662,0.00009757649,0.0001182692,0.0001854447,0.00007761036,0.00001046626],"genre_scores_gemma":[0.9851418,0.00007093196,0.01460798,0.000007906502,0.0001093952,0.000005194439,0.00001688247,0.00003049895,0.000009430622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5405727,"threshold_uncertainty_score":0.6364016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03105315708484227,"score_gpt":0.2268184074626741,"score_spread":0.1957652503778319,"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."}}