{"id":"W2054701643","doi":"10.1109/iccat.2013.6521975","title":"Classifier for drinking water quality in real time","year":2013,"lang":"en","type":"article","venue":"","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Social Fund","keywords":"Computer science; Artificial intelligence; Artificial neural network; Classifier (UML); Machine learning; Decision tree; Water quality; Data mining; k-nearest neighbors algorithm; Support vector machine; Quality (philosophy)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007652121,0.000460605,0.0006110534,0.001482286,0.0002631382,0.0009013566,0.000717932,0.0008398548,0.002567574],"category_scores_gemma":[0.003201982,0.0001264228,0.0004724893,0.0008313443,0.0001736392,0.0008521248,0.0003216803,0.0005620908,0.002118916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004906399,"about_ca_system_score_gemma":0.0004334893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001862602,"about_ca_topic_score_gemma":0.001636396,"domain_scores_codex":[0.999401,0.00007309597,0.00006357499,0.0001654084,0.0002218391,0.00007505208],"domain_scores_gemma":[0.9987227,0.0004159411,0.0001729641,0.0001459015,0.0005129787,0.00002934671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005169741,0.0005249065,0.01697473,0.0002443546,0.0001463562,0.000282412,0.0001214654,0.08345237,0.0483594,0.00292374,0.009593816,0.8368595],"study_design_scores_gemma":[0.00002740339,0.0002848723,0.01099605,0.00003082912,0.00005530412,0.0002723707,0.00006793487,0.9461102,0.03098569,0.002985597,0.00814428,0.00003940192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1799356,0.0007257349,0.799291,0.0003925564,0.0004297972,0.0002915372,0.002326942,0.008850314,0.007756643],"genre_scores_gemma":[0.792245,0.0002449038,0.1972693,0.0001811836,0.0001536035,0.0003227927,0.002944473,0.0001104044,0.006528536],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002567574,"threshold_uncertainty_score":0.008589327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0481741013792225,"score_gpt":0.3113451024679424,"score_spread":0.2631710010887199,"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."}}