{"id":"W2196431006","doi":"10.1139/cjfas-2014-0554","title":"Coho salmon escapement and trends in migration timing to a data-poor river: estimates from a Bayesian hierarchical model","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alaska Department of Fish and Game; Massachusetts Department of Fish and Game; National Science Foundation","keywords":"Escapement; Environmental science; Oncorhynchus; Bayesian probability; Population; Bayesian hierarchical modeling; Fishery; Geography; Bayesian inference; Fish <Actinopterygii>; Statistics; Mathematics; Biology; Demography","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":[0.007219983,0.0005773184,0.0007123265,0.001356233,0.0008679013,0.001280365,0.001418694,0.0007393189,0.000854657],"category_scores_gemma":[0.01838093,0.0005868868,0.001131162,0.00107528,0.0008977674,0.001621029,0.001142186,0.001146897,0.0001678512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00156172,"about_ca_system_score_gemma":0.001461659,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06551669,"about_ca_topic_score_gemma":0.07671259,"domain_scores_codex":[0.998075,0.001117285,0.0001391,0.0003908232,0.0001589362,0.0001187728],"domain_scores_gemma":[0.9927289,0.004658352,0.001239585,0.0006393498,0.0004816827,0.0002521086],"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":[0.0003811876,0.0001832614,0.2548445,0.0001226419,0.000757837,0.0001352419,0.0007891479,0.6807259,0.001487442,0.01997811,0.001622857,0.03897189],"study_design_scores_gemma":[0.00003632845,0.0000783062,0.03186758,0.00003203261,0.000102314,0.00004338693,0.0001009548,0.9530106,0.0001172084,0.01410501,0.0004655771,0.00004069013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8023448,0.0003302324,0.1943793,0.0005935983,0.00001778436,0.00007978154,0.0007402878,0.0001696406,0.001344619],"genre_scores_gemma":[0.965916,0.0001413149,0.03203056,0.00008499249,0.00002035793,0.00008512,0.0008995734,0.00002290257,0.0007990114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9344833,"threshold_uncertainty_score":0.1302707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04670455710630858,"score_gpt":0.2571097279552579,"score_spread":0.2104051708489493,"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."}}