{"id":"W3036582767","doi":"10.1016/j.scitotenv.2020.140382","title":"Analysis of a large spatiotemporal groundwater quality dataset, Ontario 2010–2017: Informing human health risk assessment and testing guidance for private drinking water wells","year":2020,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Fecal contamination and water quality","field":"Environmental Science","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kingston Health Sciences Centre; Public Health Ontario; McMaster University; University of Saskatchewan; Queen's University","funders":"","keywords":"Water quality; Aquifer; Hydrogeology; Environmental science; Groundwater; Sampling (signal processing); Hydrology (agriculture); Water well; Water resource management; Geology; Engineering; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004497697,0.0001458942,0.0002858453,0.00003524902,0.0007178784,0.00004752831,0.0006301827,0.00002515255,0.0001945083],"category_scores_gemma":[0.00005364402,0.0000785283,0.00009328288,0.0002560031,0.0008758492,0.0003910511,0.001220316,0.0001472787,0.000006742003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003747516,"about_ca_system_score_gemma":0.00002863767,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01954869,"about_ca_topic_score_gemma":0.001400408,"domain_scores_codex":[0.9977481,0.0001823937,0.0006081283,0.0003806165,0.0007185163,0.0003622921],"domain_scores_gemma":[0.9987475,0.00007235524,0.0005272768,0.000531736,0.000008286101,0.0001128271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007996915,0.0004855788,0.7061652,0.0001381523,0.000280567,6.770273e-7,0.03114582,0.07468668,0.182258,0.0008682951,0.0003158581,0.003575233],"study_design_scores_gemma":[0.0002986279,0.0001554446,0.9689951,0.00001218872,0.00009508584,4.847043e-7,0.0001383466,0.01586045,0.01367807,0.0002277479,0.0004076459,0.0001308253],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954212,0.00000466537,0.00172251,0.002076067,0.000039455,0.0004868475,0.0001171506,0.000006516683,0.0001256198],"genre_scores_gemma":[0.9973685,0.00000200524,0.002176273,0.0002436785,0.000008356655,0.00001224845,0.00003766001,0.000005176801,0.0001461357],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2628299,"threshold_uncertainty_score":0.9869802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05916812879278759,"score_gpt":0.3188091251120115,"score_spread":0.2596409963192239,"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."}}