{"id":"W1898255256","doi":"10.1109/ccece.2002.1012998","title":"Fuzzy predictive control for in-situ bioremediation","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bioremediation; Fuzzy control system; Computer science; Control system; Process (computing); Fuzzy logic; Process control; Control engineering; Process engineering; Engineering; Artificial intelligence; Contamination; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003870898,0.0004804342,0.0003783483,0.0002178392,0.0003390861,0.0006089667,0.0006637277,0.000443048,0.001302757],"category_scores_gemma":[0.0008160279,0.0001937772,0.0002171701,0.0002586453,0.0003356465,0.0004148435,0.0002979201,0.0006898933,0.0001704894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006044101,"about_ca_system_score_gemma":0.0005183289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007187491,"about_ca_topic_score_gemma":0.006025615,"domain_scores_codex":[0.9998072,0.00003868675,0.000007431823,0.00003539021,0.00009262987,0.00001878886],"domain_scores_gemma":[0.9998134,0.0000853766,0.00002523133,0.00001016827,0.00005803624,0.000007837551],"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":[0.0001660556,0.0001334115,0.0004736758,0.0003165186,0.00004961981,0.0002288704,0.0001696302,0.7661836,0.0514275,0.01475795,0.002391496,0.1637017],"study_design_scores_gemma":[0.00001394444,0.0000870484,0.0001544201,0.000007398203,0.00001559134,0.00002504542,0.000008068034,0.9844134,0.01142664,0.002010708,0.001830326,0.000007430397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0390511,0.001089296,0.9525459,0.0003057994,0.0001727178,0.00005854327,0.00005452619,0.0005390855,0.00618309],"genre_scores_gemma":[0.9428072,0.000726865,0.05081469,0.00009344696,0.00005559533,0.00007771303,0.00009530885,0.00002337148,0.005305814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007187491,"threshold_uncertainty_score":0.01429129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00490199580382967,"score_gpt":0.1982370671246023,"score_spread":0.1933350713207726,"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."}}