{"id":"W2121786986","doi":"10.1680/jees.2013.0032","title":"Probabilistic design of a riverine early warning source water monitoring system","year":2013,"lang":"en","type":"article","venue":"Journal of Environmental Engineering and Science","topic":"Water Systems and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental science; Warning system; Safeguarding; Water source; Early warning system; Probabilistic logic; Water resource management; Computer science; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.001362447,0.0007626921,0.0008924276,0.0004649096,0.0006856416,0.001352099,0.001400387,0.001107959,0.002999742],"category_scores_gemma":[0.002456944,0.0008319708,0.0004361606,0.0004458408,0.0007246935,0.0007967068,0.001183419,0.0006439961,0.0003659511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001462145,"about_ca_system_score_gemma":0.001697858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007271102,"about_ca_topic_score_gemma":0.005302313,"domain_scores_codex":[0.9986433,0.000378831,0.0000543854,0.0004136435,0.0003124636,0.0001973156],"domain_scores_gemma":[0.998647,0.0005181505,0.0003690361,0.00004828495,0.0003472405,0.00007022941],"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":[0.0001050754,0.00002185444,0.0004228155,0.00005010138,0.00001882234,0.00005819843,0.0000430842,0.9815384,0.003257967,0.003164451,0.0002080079,0.01111118],"study_design_scores_gemma":[0.0000180334,0.00008203047,0.0001792861,0.000004447841,0.00001413246,0.00001481736,0.000008381578,0.9978793,0.0005519748,0.0008515372,0.0003884324,0.000007653277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03452142,0.0001122353,0.9600985,0.0002157143,0.00001816174,0.0001483081,0.0001162559,0.0004002726,0.004369145],"genre_scores_gemma":[0.9533725,0.0001104742,0.04273249,0.00005180697,0.00001825351,0.0002348273,0.00005711575,0.00002836163,0.003394053],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007271102,"threshold_uncertainty_score":0.01445758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004764493563309369,"score_gpt":0.1428545499789615,"score_spread":0.1380900564156522,"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."}}