{"id":"W2176707711","doi":"10.1139/cjce-2014-0436","title":"Numerical study of an innovative fish ladder design for perched culverts","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Baffle; Culvert; Hydraulic jump; Turbulence; Fish <Actinopterygii>; Arch; Computational fluid dynamics; Hydraulics; Geotechnical engineering; Engineering; Marine engineering; Flow (mathematics); Environmental science; Geology; Fishery; Mechanics; Structural engineering; Mechanical engineering; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0003192036,0.0003195985,0.0004099036,0.0003870877,0.0004292813,0.0008235368,0.0005804363,0.001012027,0.002377375],"category_scores_gemma":[0.0006899087,0.0002460144,0.0003094194,0.0002944929,0.0004646652,0.0002807964,0.0004559809,0.0002398743,0.0002270187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005035254,"about_ca_system_score_gemma":0.0008625519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005585701,"about_ca_topic_score_gemma":0.005909803,"domain_scores_codex":[0.9998821,0.00002227653,0.000006530522,0.00002003681,0.00003685744,0.0000321695],"domain_scores_gemma":[0.9997154,0.00008121986,0.00005427887,0.00002766626,0.00005539484,0.00006604558],"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":[0.0001116088,0.0001326676,0.004903834,0.00008206459,0.00001698368,0.0005681995,0.00007285811,0.9672552,0.01800931,0.00145275,0.0002673737,0.007127206],"study_design_scores_gemma":[0.00003572039,0.0002513987,0.001682583,0.00001173512,0.00001037535,0.00006901226,0.0000698504,0.9950476,0.002033976,0.0001783449,0.0005990426,0.00001030976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9262887,0.0001278426,0.06152845,0.0001047583,0.00004398932,0.000104092,0.0002147106,0.0001719047,0.01141568],"genre_scores_gemma":[0.9868783,0.00005496771,0.01102714,0.00001224726,0.000001936698,0.00003546769,0.00005136847,0.00000832883,0.001930182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005585701,"threshold_uncertainty_score":0.01110637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03167328216252221,"score_gpt":0.2290936487501954,"score_spread":0.1974203665876732,"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."}}