{"id":"W2069228068","doi":"10.2166/wst.2006.143","title":"Fault detection for control of wastewater treatment plants","year":2006,"lang":"en","type":"article","venue":"Water Science & Technology","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydromantis Environmental Software Solutions (Canada)","funders":"","keywords":"Process (computing); Control (management); Monitoring and control; Fault detection and isolation; Engineering; Process control; Wastewater; Sewage treatment; Effluent; Systems engineering; Risk analysis (engineering); Computer science; Control engineering; Waste management; Artificial intelligence","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":[0.00008173379,0.00009876297,0.0001608087,0.0004181938,0.00007153869,0.000011148,0.0001568655,0.00008789943,0.000001682579],"category_scores_gemma":[0.000006392406,0.00006827807,0.00002544081,0.0002088175,0.0001527028,0.0001519599,0.00001136003,0.00002894935,0.000007471797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001395023,"about_ca_system_score_gemma":0.000006963106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001870245,"about_ca_topic_score_gemma":0.00002984474,"domain_scores_codex":[0.9992344,0.000003406745,0.0001963304,0.0001735775,0.00008258678,0.0003096635],"domain_scores_gemma":[0.9996919,0.00000783963,0.00002806363,0.0002022858,0.00005380248,0.00001610864],"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":[0.000007885438,0.000008103198,0.00009178461,0.000005396524,0.000003822748,4.865299e-7,0.00002919027,0.2261487,0.7695488,0.0001339288,0.000001232487,0.004020628],"study_design_scores_gemma":[0.0006825407,0.0001188739,0.00001835545,0.000004359281,0.000005665217,0.000008832854,0.00002196935,0.1869042,0.8102102,0.0009092095,0.001047689,0.00006807724],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.446417,0.00006093589,0.5523039,0.00007498245,0.000234885,0.0004024871,0.000009206332,0.0003481352,0.00014852],"genre_scores_gemma":[0.9981485,0.00000275577,0.001569342,0.000002312212,0.0000268357,0.0001611623,0.000002893212,0.00001183828,0.00007436459],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5517315,"threshold_uncertainty_score":0.2784299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00401464594484729,"score_gpt":0.1947553123318744,"score_spread":0.1907406663870271,"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."}}