{"id":"W2008782165","doi":"10.1002/bit.10336","title":"Modeling aerobic carbon source degradation processes using titrimetric data and combined respirometric–titrimetric data: Experimental data and model structure","year":2002,"lang":"en","type":"article","venue":"Biotechnology and Bioengineering","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Respirometer; Respirometry; Chemistry; Degradation (telecommunications); Aeration; Activated sludge; Carbon fibers; Substrate (aquarium); Biomass (ecology); Base (topology); Chromatography; Oxygen; Environmental chemistry; Sewage treatment; Organic chemistry; Environmental engineering; Materials science; Environmental science","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":[0.0005738203,0.001301011,0.0009334401,0.0004989285,0.0002592074,0.001038709,0.001353453,0.001680439,0.001230451],"category_scores_gemma":[0.001108264,0.0004135226,0.001192787,0.000454723,0.0002883185,0.001062514,0.0004559083,0.000934878,0.000531978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001280603,"about_ca_system_score_gemma":0.0008851194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008574562,"about_ca_topic_score_gemma":0.004305015,"domain_scores_codex":[0.9998222,0.00003139384,0.0000152589,0.00005676287,0.00005380503,0.00002067938],"domain_scores_gemma":[0.9995153,0.0002646693,0.00006280502,0.00002335532,0.000120214,0.0000136886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005207869,0.00005116265,0.0009653656,0.0002055808,0.00003601947,0.00005649951,0.00003756708,0.9828792,0.011224,0.0008970719,0.00009223217,0.003503093],"study_design_scores_gemma":[0.000004810287,0.00002710802,0.0002502929,0.000005282423,0.00001192315,0.00001119339,0.000004475393,0.9961539,0.002884129,0.0003676937,0.0002718456,0.000007343358],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4348937,0.00133505,0.547711,0.0003900883,0.000101953,0.0005295687,0.002091197,0.001039197,0.01190822],"genre_scores_gemma":[0.9452909,0.001139869,0.04414535,0.00006606762,0.00002624537,0.001097607,0.001470936,0.000128782,0.006634161],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008574562,"threshold_uncertainty_score":0.01704931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05699112184431868,"score_gpt":0.243766252696882,"score_spread":0.1867751308525633,"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."}}