{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008336015,0.0001738391,0.0003587013,0.000128094,0.0000938819,0.00001063727,0.000177791,0.0001659453,0.001325871],"category_scores_gemma":[0.0004438576,0.0001552522,0.00003847071,0.0003985443,0.0001747244,0.0001301896,0.0003105634,0.0003810144,0.00007195394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006597746,"about_ca_system_score_gemma":0.0000502139,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1868014,"about_ca_topic_score_gemma":0.9857987,"domain_scores_codex":[0.9982432,0.0004002262,0.0002859041,0.0003901316,0.0002704496,0.0004101202],"domain_scores_gemma":[0.9990649,0.0005915135,0.000108101,0.0001667006,0.000002139168,0.00006669224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002861227,0.0003520412,0.994269,0.00001743894,0.00001995565,0.000212692,0.0006278213,0.001296642,0.0001527295,0.0002551854,0.002056747,0.000711128],"study_design_scores_gemma":[0.0004716346,0.0002742661,0.9966998,0.00002285103,0.00001072533,0.0000020114,0.000142023,0.0005066764,0.0006110054,0.0005849643,0.000486535,0.000187492],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838899,0.000001027889,0.00003107292,0.000411816,0.0001581655,0.0004603612,0.000001012957,0.00001873163,0.0150279],"genre_scores_gemma":[0.9976414,0.000002719881,0.0001721097,0.001875418,0.000003962753,0.00005352254,0.000004477622,0.000006101829,0.0002402334],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7989973,"threshold_uncertainty_score":0.9995871,"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."}}