{"id":"W1987067526","doi":"10.1016/j.cej.2004.01.030","title":"Biofiltration of xylene emissions: bioreactor response to variations in the pollutant inlet concentration and gas flow rate","year":2004,"lang":"en","type":"article","venue":"Chemical Engineering Journal","topic":"Odor and Emission Control Technologies","field":"Chemical Engineering","cited_by":79,"is_retracted":false,"has_abstract":false,"ca_institutions":"Biorem Technologies (Canada); Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biofilter; Carbon dioxide; Pollutant; Inlet; Chemistry; Xylene; Volumetric flow rate; Environmental chemistry; Environmental engineering; Filter (signal processing); Biodegradation; Bioreactor; Toluene; Pulp and paper industry; Environmental science; Mechanics; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004838639,0.0001357689,0.0001784828,0.00009409783,0.00003934692,0.000039853,0.0001837246,0.0001329377,0.00001602432],"category_scores_gemma":[0.002518564,0.00009830151,0.00004822234,0.0003362041,0.00002482178,0.0001132317,0.0000286774,0.0003998691,0.000001721477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001075969,"about_ca_system_score_gemma":0.00005015875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003456039,"about_ca_topic_score_gemma":2.232e-7,"domain_scores_codex":[0.9990916,0.00002275963,0.0003715874,0.0001297179,0.0001646008,0.0002196956],"domain_scores_gemma":[0.9993601,0.0002657837,0.0000620717,0.0001478428,0.00004699071,0.0001172172],"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":[0.0001011919,0.00002577413,0.00002782366,0.00001158131,0.000009445983,0.00000787168,0.0004391202,0.02064248,0.9768387,0.0003944514,0.00003127067,0.001470262],"study_design_scores_gemma":[0.001072132,0.00005731793,0.0008550109,0.0002223773,0.00001574066,0.00009667822,0.0001154774,0.04768661,0.9488654,0.0005045465,0.0003463666,0.0001623209],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8669226,0.0002016988,0.1273871,0.005156152,0.00009727014,0.0001271021,0.00001226824,0.00007904586,0.00001684097],"genre_scores_gemma":[0.9861999,0.00004780393,0.01357408,0.00006261928,0.00008500372,0.000009981851,0.000003079146,0.00001310045,0.000004445625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1192773,"threshold_uncertainty_score":0.4008619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009728926811033132,"score_gpt":0.2253332980978439,"score_spread":0.2156043712868108,"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."}}