{"id":"W2023199188","doi":"10.1061/40856(200)91","title":"Managing Water Levels and Flows for Improved Economical, Environmental, and Ecological Benefits in Lake Ontario and in the St. Lawrence River","year":2006,"lang":"en","type":"article","venue":"","topic":"Aquatic Invertebrate Ecology and Behavior","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hydropower; Commission; Recreation; Shore; Balance of nature; Environmental resource management; Flood myth; Drainage basin; Water resources; Environmental science; Water supply; Flood control; Environmental planning; Business; Geography; Ecology; Fishery; Environmental engineering","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":[0.0005374462,0.00009022694,0.00010294,0.0004114412,0.003087076,0.001772568,0.0005557201,0.0004578166,0.001346639],"category_scores_gemma":[0.001285866,0.0001213588,0.0001197228,0.001019503,0.002121246,0.0005813947,0.0006806666,0.0003001141,0.00006274357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0398689,"about_ca_system_score_gemma":0.0245412,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9603897,"about_ca_topic_score_gemma":0.9939991,"domain_scores_codex":[0.999238,0.0001688455,0.00001974112,0.00004888695,0.0002234621,0.0003010651],"domain_scores_gemma":[0.9995271,0.00006289897,0.00009610615,0.00001168723,0.0001450735,0.000157035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004606133,0.000344471,0.6558291,0.0003873711,0.0001774931,0.001508578,0.03835008,0.01939066,0.01265035,0.07470307,0.03115028,0.1650479],"study_design_scores_gemma":[0.0000399625,0.0001948277,0.8872237,0.00007727851,0.00007861324,0.0001315662,0.03568884,0.005957478,0.001485984,0.004062038,0.06498951,0.0000702414],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9703215,0.0003779208,0.0005620148,0.00464795,0.000008696042,0.00004257214,0.0001217107,0.00002613867,0.0238914],"genre_scores_gemma":[0.9930627,0.0002914526,0.0007343962,0.0001738208,0.000003671009,0.00001293094,0.00003724023,0.000004315814,0.005679509],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.0398689,"threshold_uncertainty_score":0.2892705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01549691818381843,"score_gpt":0.1960721605971991,"score_spread":0.1805752424133807,"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."}}