{"id":"W2037508390","doi":"10.1080/07011784.2013.830371","title":"Demonstration of a methodology for setting ecological flow and water level targets","year":2013,"lang":"en","type":"article","venue":"Canadian Water Resources Journal / Revue canadienne des ressources hydriques","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Environmental science; Habitat; Streamflow; Environmental resource management; Flow (mathematics); Process (computing); Ecosystem health; Ecosystem; Water resources; River ecosystem; Computer science; Hydrology (agriculture); Water resource management; Ecology; Ecosystem services; Geography; Drainage basin; Geology; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.009493216,0.0008665682,0.000469051,0.002486115,0.001294156,0.002342917,0.001512785,0.0009458466,0.004983002],"category_scores_gemma":[0.01840117,0.0005188786,0.0007299369,0.001819048,0.001184021,0.001887723,0.002670899,0.001284215,0.001331685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001476384,"about_ca_system_score_gemma":0.005294193,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01279502,"about_ca_topic_score_gemma":0.02089298,"domain_scores_codex":[0.9954543,0.002222269,0.0003944738,0.0005732741,0.001216843,0.0001388818],"domain_scores_gemma":[0.9919379,0.003961573,0.0008062324,0.001043965,0.002058898,0.0001913663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001161742,0.0003360672,0.01330316,0.0005762869,0.00009600293,0.0006150897,0.00616877,0.1011601,0.01289947,0.2917931,0.01003638,0.5628994],"study_design_scores_gemma":[0.0001543235,0.0005030395,0.007058104,0.0003877362,0.00008406987,0.0007891027,0.002638296,0.6615905,0.02068924,0.1945905,0.1113053,0.0002097805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001448526,0.000007613364,0.9959258,0.00006752484,0.000009082593,0.0002411813,0.00008596344,0.0003281858,0.001886142],"genre_scores_gemma":[0.02058437,0.00002244092,0.9780409,0.00002045612,0.000003604462,0.000506764,0.00008797587,0.00006294972,0.0006705073],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.987205,"threshold_uncertainty_score":0.05020553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03398335446633321,"score_gpt":0.2217223078135885,"score_spread":0.1877389533472552,"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."}}