{"id":"W2252944900","doi":"10.1007/s11356-016-6106-6","title":"A Bayesian-based two-stage inexact optimization method for supporting stream water quality management in the Three Gorges Reservoir region","year":2016,"lang":"en","type":"article","venue":"Environmental Science and Pollution Research","topic":"Water resources management and optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"National Science Fund for Distinguished Young Scholars; Major Science and Technology Program for Water Pollution Control and Treatment; Higher Education Discipline Innovation Project; National Natural Science Foundation of China","keywords":"Three gorges; Stage (stratigraphy); Ecotoxicology; Water quality; Bayesian probability; Environmental science; Quality (philosophy); Water resource management; Hydrology (agriculture); Computer science; Ecology; Geology; Artificial intelligence; Biology; Geotechnical engineering","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":[0.001500361,0.0007926988,0.00151788,0.0006172877,0.0007562314,0.001238575,0.001747165,0.002107721,0.002192127],"category_scores_gemma":[0.003018872,0.001031564,0.0007439414,0.0004840975,0.0007099488,0.001075875,0.001479977,0.001280317,0.0003388365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006510194,"about_ca_system_score_gemma":0.002811176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02578263,"about_ca_topic_score_gemma":0.02318072,"domain_scores_codex":[0.9994828,0.0001663522,0.00003970177,0.0000885734,0.000159913,0.00006274993],"domain_scores_gemma":[0.9990095,0.0004283693,0.0001128512,0.00005812977,0.0003030727,0.00008798084],"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":[0.00007676768,0.00005373829,0.0005882989,0.00003863167,0.00002797865,0.00004783422,0.0000420846,0.9667444,0.001343851,0.001343962,0.0004269138,0.02926562],"study_design_scores_gemma":[0.000004289137,0.000006731139,0.0000535591,0.000001252677,0.000001755752,0.00000205342,0.000002470367,0.9996746,0.00008907701,0.0001027993,0.00005909919,0.000002495017],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06695215,0.0001336132,0.9292762,0.0003077417,0.0000658346,0.00006388868,0.00008298529,0.0005978476,0.002519753],"genre_scores_gemma":[0.6206111,0.0001113764,0.3752358,0.0001499432,0.0000584093,0.0001813256,0.0002118512,0.0001513256,0.003288862],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02578263,"threshold_uncertainty_score":0.05126512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05159369678217476,"score_gpt":0.3454523711341316,"score_spread":0.2938586743519569,"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."}}