{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001935621,0.0001068853,0.0001649797,0.00004101491,0.0001294139,0.000005069952,0.00008665882,0.0001038346,0.000006001153],"category_scores_gemma":[0.0002241948,0.0001032334,0.00003019839,0.0001669701,0.00009112383,0.000198452,0.0001060946,0.0002852582,7.000666e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006152946,"about_ca_system_score_gemma":0.00000459163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001484932,"about_ca_topic_score_gemma":0.002819707,"domain_scores_codex":[0.9991919,0.00002690051,0.0002685251,0.0002108763,0.0001683321,0.0001334962],"domain_scores_gemma":[0.9996011,0.00007460298,0.0002007461,0.00007657123,0.00002288648,0.00002410732],"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":[0.0001368949,0.00004972319,0.1523127,0.00003465136,0.00003275816,4.640109e-7,0.002445423,0.7969424,0.04391137,0.0006252202,0.00003627469,0.003472098],"study_design_scores_gemma":[0.0002009373,0.00003025028,0.1295689,0.0000142402,0.00001887645,6.374047e-7,0.0002482821,0.8665287,0.0001218633,0.00318174,2.530242e-7,0.0000852771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955142,0.00003573981,0.003144458,0.00007670136,0.00004573348,0.0001898484,0.000003447589,0.00002447682,0.0009653807],"genre_scores_gemma":[0.993504,0.000006694042,0.006316541,0.00005255921,0.000008690725,0.000006894951,0.000008843761,0.00001025123,0.00008553039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06958635,"threshold_uncertainty_score":0.4209738,"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."}}