{"id":"W2620837839","doi":"10.1007/s10661-017-5989-0","title":"Risk-based framework for optimizing residual chlorine in large water distribution systems","year":2017,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Water Systems and Optimization","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"King Abdulaziz City for Science and Technology","keywords":"Residual; Water quality; Environmental science; Water supply; Risk assessment; Environmental engineering; Computer science; Water resource management; Computer security","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":[0.003417826,0.001787607,0.002113231,0.001352858,0.0005738961,0.002512041,0.002365676,0.002405067,0.003480704],"category_scores_gemma":[0.005245513,0.001198344,0.001246886,0.001091437,0.001118622,0.001682202,0.001711263,0.001712183,0.0002660998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003285303,"about_ca_system_score_gemma":0.003421161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02460564,"about_ca_topic_score_gemma":0.01607029,"domain_scores_codex":[0.998584,0.0005734086,0.00004393465,0.0001767573,0.0003942179,0.000227677],"domain_scores_gemma":[0.9983745,0.0009471336,0.0001462702,0.00006666964,0.0003826328,0.00008285793],"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":[0.000007452071,0.0000092084,0.00005344043,0.0000129164,0.0000107734,0.00001252242,0.000005352313,0.9962133,0.0000778816,0.002463948,0.0001385221,0.0009946638],"study_design_scores_gemma":[0.000003334226,0.000004854066,0.00002284655,0.000002428715,0.00000403288,0.000002324045,0.000002720312,0.9984126,0.00004606284,0.001412764,0.00008403716,0.000001974012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02140149,0.0006205552,0.9686284,0.0006918702,0.00005590971,0.0001123164,0.0002220719,0.0003013634,0.007965963],"genre_scores_gemma":[0.8940394,0.0005400064,0.09379289,0.0002473038,0.0001025371,0.0003287278,0.0003027295,0.0002091797,0.01043728],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02460564,"threshold_uncertainty_score":0.0489248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01075736767088362,"score_gpt":0.2489785929381836,"score_spread":0.2382212252672999,"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."}}