{"id":"W1907395388","doi":"10.1111/j.1939-7445.2010.00077.x","title":"A MODEL OF CHINOOK SALMON POPULATION DYNAMICS INCORPORATING SIZE‐SELECTIVE EXPLOITATION AND INHERITANCE OF POLYGENIC CORRELATED TRAITS","year":2010,"lang":"en","type":"article","venue":"Natural Resource Modeling","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of British Columbia; Alaska Department of Fish and Game; National Oceanic and Atmospheric Administration; Simon Fraser University; U.S. Department of Commerce","keywords":"Chinook wind; Population; Fishery; Heritability; Biology; Population size; Selection (genetic algorithm); Fisheries management; Fish <Actinopterygii>; Fecundity; Effective population size; Ecology; Oncorhynchus; Evolutionary biology; Fishing; Computer science; Demography; Machine learning; Genetic variation","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001023354,0.0006714656,0.0009188238,0.0005745934,0.0007338931,0.001293659,0.002075543,0.001534753,0.004131321],"category_scores_gemma":[0.002502149,0.000598782,0.001116957,0.0007169795,0.001275986,0.001211973,0.000804048,0.0009621837,0.0004267933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001745734,"about_ca_system_score_gemma":0.001724566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06187595,"about_ca_topic_score_gemma":0.02669973,"domain_scores_codex":[0.9996636,0.000114091,0.00001296355,0.00009496701,0.00003264821,0.00008172417],"domain_scores_gemma":[0.9987398,0.0006218391,0.0002475599,0.00005254663,0.0001669944,0.0001712839],"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":[0.00006415432,0.00003972188,0.004583089,0.00001857292,0.00006193991,0.0001577627,0.00006796712,0.9774339,0.0006333709,0.01540039,0.0004392811,0.001099939],"study_design_scores_gemma":[0.00002660682,0.00002516197,0.0007898752,0.000003162415,0.00001680853,0.00001729602,0.00001563296,0.9971656,0.00002272334,0.001806875,0.0001025852,0.000007628864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8653084,0.0002611084,0.1195824,0.001521064,0.00007793208,0.00007626668,0.001322112,0.0002746304,0.01157594],"genre_scores_gemma":[0.9856803,0.000150547,0.004351786,0.00007965946,0.00002995217,0.0001198586,0.000328924,0.00002782217,0.00923105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06187595,"threshold_uncertainty_score":0.1230316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009123017081742586,"score_gpt":0.2159651455331862,"score_spread":0.2068421284514436,"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."}}