{"id":"W3010589457","doi":"10.1139/cjfas-2019-0281","title":"Evaluation of methods for spawner–recruit analysis in mixed-stock Pacific salmon fisheries","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Fisheries and Oceans Canada","funders":"","keywords":"Oncorhynchus; Stock (firearms); Chinook wind; Fishery; Mixed model; Stock assessment; Population; Biodiversity; Fisheries management; Geography; Ecology; Biology; Statistics; Fish <Actinopterygii>; Fishing; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.05130601,0.001266757,0.00104018,0.002156615,0.0008727683,0.001811847,0.002469466,0.001239445,0.001975489],"category_scores_gemma":[0.1083528,0.0009210772,0.001785976,0.001371232,0.0009512483,0.002637974,0.002262271,0.001812227,0.0003442605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001979399,"about_ca_system_score_gemma":0.003848223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01874082,"about_ca_topic_score_gemma":0.02074554,"domain_scores_codex":[0.9818517,0.01369789,0.0008210603,0.001446531,0.001977744,0.0002051026],"domain_scores_gemma":[0.8825743,0.1016446,0.004167105,0.004133596,0.00682724,0.0006532071],"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":[0.0007666784,0.0004769587,0.07951678,0.0004413356,0.001487278,0.0001250925,0.0006640211,0.6805759,0.00254339,0.01423949,0.0010983,0.2180647],"study_design_scores_gemma":[0.0000457842,0.00009786083,0.003697592,0.00003444788,0.00003607688,0.00002206244,0.00006436166,0.9913298,0.0006363512,0.003607801,0.0004014456,0.00002639833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09590941,0.0004563982,0.900833,0.000256335,0.00004754404,0.0004339764,0.000364716,0.0009278089,0.0007708872],"genre_scores_gemma":[0.3596122,0.000325347,0.6378926,0.00009287921,0.00002812414,0.0007540985,0.0006006174,0.0002562065,0.0004379442],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05130601,"threshold_uncertainty_score":0.2713354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08062374475883935,"score_gpt":0.3133275350136116,"score_spread":0.2327037902547723,"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."}}