{"id":"W1483977642","doi":"10.2166/wst.2002.0619","title":"Respirometry-based on-line model parameter estimation at a full-scale WWTP","year":2002,"lang":"en","type":"article","venue":"Water Science & Technology","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Respirometer; Respirometry; Sewage treatment; Wastewater; Engineering; Activated sludge; Scale (ratio); Estimation theory; Sewage sludge; Full scale; Environmental science; Process engineering; Environmental engineering; Computer science; Algorithm","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":[0.0009412052,0.0007749962,0.0007673023,0.000334877,0.0003468478,0.0008545092,0.0008777384,0.0009276541,0.0008886614],"category_scores_gemma":[0.003116655,0.0003672612,0.0004934702,0.0003314897,0.0002413202,0.0008250299,0.0004910034,0.0007009512,0.0003481129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007762715,"about_ca_system_score_gemma":0.0006744309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00819038,"about_ca_topic_score_gemma":0.008335782,"domain_scores_codex":[0.9994797,0.0001771555,0.00003083331,0.0001559026,0.0001191949,0.00003727971],"domain_scores_gemma":[0.9987141,0.0006820861,0.0001133037,0.0002230831,0.0002400845,0.00002723882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008337689,0.000841988,0.0157127,0.0003387897,0.0001715027,0.0002065865,0.0003654589,0.6153808,0.2300148,0.0002740817,0.0005504788,0.135309],"study_design_scores_gemma":[0.00008190739,0.0005844985,0.0118554,0.000007585478,0.00005696753,0.00006077548,0.00008646575,0.9082818,0.07805797,0.000321399,0.0005607067,0.00004450281],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8657036,0.00006092169,0.1307946,0.00007748342,0.000009416701,0.0001332,0.0004147379,0.001749019,0.001057033],"genre_scores_gemma":[0.9733064,0.0000288636,0.02573119,0.00001284751,0.000002916792,0.0001057461,0.000352772,0.00006155414,0.0003977834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00819038,"threshold_uncertainty_score":0.01628542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04071266915947302,"score_gpt":0.2671161734805507,"score_spread":0.2264035043210777,"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."}}