{"id":"W2030385104","doi":"10.3182/20090712-4-tr-2008.00161","title":"Early determination of toxicant concentration in water supply using MHE","year":2009,"lang":"en","type":"article","venue":"IFAC Proceedings Volumes","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Extended Kalman filter; Toxicant; Kalman filter; Estimator; Moving horizon estimation; Water supply; Computer science; Environmental science; Estimation; Control theory (sociology); Warning system; Engineering; Control engineering; Environmental engineering; Chemistry; Control (management); Mathematics; Artificial intelligence; Systems engineering; Statistics","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":[0.0002693399,0.0002360071,0.000293546,0.0002563704,0.0001968217,0.0003631721,0.0002497947,0.0005065915,0.001320065],"category_scores_gemma":[0.0004458491,0.0001738592,0.0002034984,0.0001380384,0.0002852146,0.0005377897,0.0003553766,0.0004589127,0.0006663463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002409714,"about_ca_system_score_gemma":0.0001784756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000879176,"about_ca_topic_score_gemma":0.001926279,"domain_scores_codex":[0.9996781,0.00004181434,0.00001009732,0.00006050576,0.0001630124,0.00004636183],"domain_scores_gemma":[0.9997961,0.00008373228,0.00002130406,0.00001619862,0.00006791778,0.00001469804],"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":[0.0003654925,0.00002369382,0.004236689,0.00007422257,0.000007613304,0.0000745457,0.00006818865,0.0001482288,0.9823027,0.0001732397,0.0001775808,0.01234775],"study_design_scores_gemma":[0.000004536531,0.0001886284,0.005952945,0.000008021315,0.000007445607,0.00007067201,0.00006596194,0.001669972,0.9896889,0.00008299559,0.002252039,0.000007920866],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9040195,0.001659517,0.08346602,0.0004042795,0.0002042055,0.0001986322,0.0006627879,0.0006941176,0.008690977],"genre_scores_gemma":[0.9689322,0.0003931153,0.0214051,0.0001379374,0.00003007072,0.00004996728,0.0001359113,0.00001734971,0.008898474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001320065,"threshold_uncertainty_score":0.004416049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01137929218901233,"score_gpt":0.2356249782692075,"score_spread":0.2242456860801952,"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."}}