{"id":"W2808149924","doi":"10.1007/s10661-018-6769-1","title":"Investigating the management performance of disinfection analysis of water distribution networks using data mining approaches","year":2018,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Water Systems and Optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Artificial neural network; Support vector machine; Perceptron; Residual; Multilayer perceptron; Data mining; Mean squared error; Artificial intelligence; Computer science; Machine learning; Statistics; Mathematics; 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":[0.003759053,0.0009686619,0.0007042412,0.001732093,0.00041935,0.00152879,0.0007497161,0.0008949084,0.0003776591],"category_scores_gemma":[0.008988801,0.0003117259,0.0008149667,0.001023711,0.0002976515,0.001605278,0.0004794528,0.0005640548,0.0000799897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001194506,"about_ca_system_score_gemma":0.00122724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01438586,"about_ca_topic_score_gemma":0.008942572,"domain_scores_codex":[0.998882,0.0004974852,0.000106027,0.0001922998,0.0002040196,0.0001182533],"domain_scores_gemma":[0.992949,0.005119039,0.000701959,0.0003615505,0.0007237286,0.0001447195],"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":[0.0008714118,0.0009816401,0.06650906,0.0001929214,0.0005062335,0.000105174,0.00008884171,0.8327272,0.005549301,0.001276926,0.0007078611,0.09048352],"study_design_scores_gemma":[0.000007929247,0.0001221079,0.003851223,0.000005037109,0.00004084845,0.00001242626,0.000057907,0.992708,0.00258629,0.0004957742,0.0001076894,0.000004832158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9654655,0.0004756653,0.03184912,0.0004975373,0.00002287004,0.00005838946,0.00029097,0.0002039289,0.001135906],"genre_scores_gemma":[0.9877675,0.000146961,0.01147094,0.0000242579,0.00001136832,0.00001729588,0.0002907868,0.000007458885,0.0002635471],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01438586,"threshold_uncertainty_score":0.02860421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03556896594372323,"score_gpt":0.2342343095026294,"score_spread":0.1986653435589062,"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."}}