{"id":"W2494593019","doi":"10.1139/cjfas-2015-0520","title":"Seasonal and spatial fluctuations in <i>Oncorhynchus</i> trout diet in a temperate mixed-forest watershed","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"California Department of Fish and Wildlife; Oregon State University","keywords":"Trout; Predation; Benthic zone; Tributary; Oncorhynchus; Biomass (ecology); Invertebrate; Biology; Ecology; Fishery; Environmental science; Temperate climate; Watershed; Salmonidae; Seasonality; Rainbow trout; Geography; 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":[0.0001831876,0.0001009044,0.0001657196,0.0004643471,0.0003654191,0.0004127076,0.0001836087,0.0001410812,0.0005901187],"category_scores_gemma":[0.0003288522,0.0001507559,0.0001225242,0.0005153509,0.0003312887,0.0002449966,0.0003118261,0.00016517,0.00009536952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008059017,"about_ca_system_score_gemma":0.0004256167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07410321,"about_ca_topic_score_gemma":0.2294813,"domain_scores_codex":[0.9998984,0.00001172201,0.000008906498,0.00003267395,0.00002041109,0.00002783027],"domain_scores_gemma":[0.9996847,0.00003052397,0.0001391053,0.0000129878,0.00005028858,0.00008250493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001265097,0.00005551328,0.9916967,0.000005828312,0.00003038128,0.00007079627,0.0003333144,0.0001100258,0.005927118,0.00001952491,0.00008956122,0.001534643],"study_design_scores_gemma":[0.000001165464,0.00001089739,0.9996023,7.294403e-7,0.000003236892,0.00001187627,0.0001804284,0.00008788557,0.00006334339,0.00000363441,0.00003349793,9.930941e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998504,0.000004229102,0.00001370065,0.000003243351,2.733297e-7,8.839421e-7,0.0000474512,0.000001292024,0.00007854638],"genre_scores_gemma":[0.9996756,0.000009209814,0.0000505364,0.000005515215,0.000001034576,0.000003205854,0.0001342044,0.000001526993,0.0001192177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07410321,"threshold_uncertainty_score":0.1473438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00987552747397182,"score_gpt":0.1963195856741532,"score_spread":0.1864440582001814,"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."}}