{"id":"W2085763697","doi":"10.1016/j.ecolind.2014.07.018","title":"Benthic macroinvertebrate flow sensitivity as a tool to assess effects of hydropower related ramping activities in streams in Ontario (Canada)","year":2014,"lang":"en","type":"article","venue":"Ecological Indicators","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"Impact; University of Waterloo; Fisheries and Oceans Canada; St. Lawrence River Institute of Environmental Sciences; University of New Brunswick","funders":"University of Waterloo; Canadian Foundation for Climate and Atmospheric Sciences; Nature Conservancy; Ontario Innovation Trust","keywords":"Hydropower; Environmental science; Hydroelectricity; River ecosystem; Benthic zone; STREAMS; Streamflow; Hydrology (agriculture); Water resource management; Environmental resource management; Ecosystem; Ecology; Drainage basin; Computer science; Geography; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.0004522895,0.0002112673,0.000196491,0.0009852618,0.001453014,0.0008277506,0.0005030929,0.0002399654,0.0006114065],"category_scores_gemma":[0.001246782,0.0002320353,0.0001815231,0.001825462,0.000710941,0.0003123772,0.0005541692,0.0003051403,0.00008583605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.010931,"about_ca_system_score_gemma":0.008914033,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9884847,"about_ca_topic_score_gemma":0.9979011,"domain_scores_codex":[0.9996013,0.000060857,0.00002963309,0.00005543894,0.0001468027,0.0001059237],"domain_scores_gemma":[0.9989765,0.00008920314,0.0002278849,0.00001999535,0.0004350022,0.0002514216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004308255,0.00002201342,0.9923406,0.00002175677,0.00002792055,0.00005197699,0.001198551,0.000203544,0.0004583866,0.00003682021,0.0002846202,0.00531076],"study_design_scores_gemma":[0.000001691301,0.00001140185,0.9985641,0.000006264232,0.000006165432,0.00001045829,0.0009240236,0.0001540446,0.00004438265,0.000007340347,0.000267907,0.000002306153],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998422,0.0001244834,0.00008547433,0.00005235386,0.000002460421,0.00001733436,0.0004186372,0.000004370549,0.0008728657],"genre_scores_gemma":[0.9982817,0.000175528,0.0003145952,0.00002169552,0.000001473985,0.00001165749,0.0002582196,0.000001853155,0.0009333999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01151532,"threshold_uncertainty_score":0.07931036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006158880479207502,"score_gpt":0.2039521556987487,"score_spread":0.1977932752195412,"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."}}