{"id":"W2133274918","doi":"10.1139/f05-149","title":"Predicting cutthroat trout (<i>Oncorhynchus clarkii</i>) abundance in high-elevation streams: revisiting a model of translocation success","year":2005,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Forest Service; U.S. Fish and Wildlife Service","keywords":"Electrofishing; Trout; STREAMS; Oncorhynchus; Abundance (ecology); Population; Habitat; Environmental science; Ecology; Fishery; Relative species abundance; Biology; Fish <Actinopterygii>","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":[0.001396937,0.0004848738,0.0003802119,0.0003803018,0.0004791513,0.0009444184,0.0007969118,0.0006087921,0.0005358763],"category_scores_gemma":[0.002652315,0.0004878729,0.0004171774,0.0003125151,0.0004569969,0.0007333335,0.0004729371,0.0005062823,0.0001005931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001585929,"about_ca_system_score_gemma":0.002201862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1498849,"about_ca_topic_score_gemma":0.1472649,"domain_scores_codex":[0.9997591,0.00008501188,0.00001501571,0.00006759117,0.00002515112,0.00004809456],"domain_scores_gemma":[0.9988575,0.0006643828,0.0001861942,0.00002806406,0.0001295793,0.0001342872],"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":[0.0001308581,0.0001679534,0.4086875,0.00002208406,0.0001148399,0.00009002132,0.00007448723,0.5817816,0.00100289,0.0003655881,0.0004426192,0.007119705],"study_design_scores_gemma":[0.00001725737,0.00007602791,0.03141449,0.000003679382,0.00002684,0.00002681536,0.00006761539,0.9678407,0.0001560067,0.0002990812,0.00006379033,0.000007701082],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958907,0.00003563339,0.003679205,0.0001351298,0.000004886984,0.000008631838,0.00005610053,0.00003158467,0.0001580781],"genre_scores_gemma":[0.9974577,0.00003864478,0.002135716,0.00002120823,0.000006937898,0.00000909221,0.0001207935,0.000004905656,0.0002051003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1498849,"threshold_uncertainty_score":0.2980249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0139967030782595,"score_gpt":0.213757039390993,"score_spread":0.1997603363127335,"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."}}