{"id":"W2084248257","doi":"10.1139/s07-012","title":"Neural network models of Cryptosporidium parvum inactivation by chlorine dioxide and ozone","year":2007,"lang":"en","type":"article","venue":"Journal of Environmental Engineering and Science","topic":"Parasitic Infections and Diagnostics","field":"Immunology and Microbiology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Chlorine dioxide; Artificial neural network; Disinfectant; Ozone; Residual; Environmental science; Cryptosporidium parvum; Variable (mathematics); Biological system; Chemistry; Computer science; Artificial intelligence; Biology; Mathematics; Microbiology; Algorithm; Inorganic chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0006035101,0.0006895034,0.0004632408,0.0004428308,0.0002868801,0.0004572168,0.001217059,0.0009559605,0.001198478],"category_scores_gemma":[0.00160706,0.0003490038,0.000565109,0.0003026022,0.0003660537,0.0006463896,0.0003137597,0.0007164819,0.0001631192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001147456,"about_ca_system_score_gemma":0.0007730625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02511431,"about_ca_topic_score_gemma":0.01946009,"domain_scores_codex":[0.9998842,0.00002456536,0.00000697753,0.00002882749,0.00002890826,0.00002637137],"domain_scores_gemma":[0.9993929,0.0003393671,0.00007232623,0.00001332093,0.0001619278,0.0000201909],"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":[0.00001687086,0.000008025345,0.000286654,0.000006712305,0.000005986804,0.000008551397,0.000006680158,0.9972083,0.0003082654,0.0003140045,0.00003344991,0.001796549],"study_design_scores_gemma":[0.000001587474,0.000007891001,0.00008713139,8.343635e-7,0.000002527335,0.000001797011,9.945887e-7,0.9995412,0.000145979,0.0001877334,0.00002096247,0.000001435529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5576437,0.0008117761,0.4351153,0.0004047725,0.00009441253,0.00009407028,0.0002988607,0.0004773872,0.005059704],"genre_scores_gemma":[0.9694921,0.0003347743,0.02346218,0.00003685691,0.00001734295,0.0001305483,0.0001623753,0.00002219806,0.006341679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02511431,"threshold_uncertainty_score":0.04993623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004589099362772173,"score_gpt":0.1904639370030029,"score_spread":0.1858748376402307,"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."}}