{"id":"W2052733020","doi":"10.1139/f00-074","title":"Evaluating spatially explicit metrics of stream energy gradients using hydrodynamic model simulations","year":2000,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Spatial variability; Flow (mathematics); Metric (unit); Spatial ecology; Spatial heterogeneity; Channel (broadcasting); Habitat; Environmental science; STREAMS; Biological system; Hydrology (agriculture); Ecology; Computer science; Geology; Statistics; Mathematics; Geometry; Geotechnical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.000982335,0.0006050746,0.000552077,0.001120336,0.0003467627,0.0009654242,0.0006722058,0.0009169696,0.0006886121],"category_scores_gemma":[0.00475583,0.000396424,0.0005072452,0.000884434,0.0005062743,0.001012309,0.0005409574,0.0004434834,0.00006632785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001506937,"about_ca_system_score_gemma":0.001036166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02880337,"about_ca_topic_score_gemma":0.01900803,"domain_scores_codex":[0.9996973,0.0001367647,0.00003137447,0.00004888107,0.00004774506,0.00003791026],"domain_scores_gemma":[0.9976754,0.001588593,0.0002150304,0.000156436,0.0002551782,0.0001093281],"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":[0.0000135184,0.00002554469,0.001940494,0.000005700355,0.00001071499,0.00001020331,0.00001079899,0.9966713,0.0002106265,0.00028311,0.00002924392,0.0007888442],"study_design_scores_gemma":[0.000005830309,0.0000117243,0.0005050921,0.000001473363,0.000002496151,0.000002078342,0.000007241558,0.9991499,0.0001530655,0.0001287584,0.00002880626,0.000003500139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9751864,0.00007040856,0.02225158,0.00008591841,0.00001152493,0.00005752968,0.0004231161,0.000230234,0.001683325],"genre_scores_gemma":[0.9876599,0.0000449679,0.01173333,0.00001245414,0.000003912932,0.00006137398,0.0002649211,0.00002402692,0.0001952138],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02880337,"threshold_uncertainty_score":0.05727142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04259774339077017,"score_gpt":0.2645863933751967,"score_spread":0.2219886499844266,"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."}}