{"id":"W4289336648","doi":"10.1002/eap.2709","title":"Chinook salmon diversity contributes to fishery stability and trade‐offs with mixed‐stock harvest","year":2022,"lang":"en","type":"article","venue":"Ecological Applications","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Eagle Ridge Hospital; Simon Fraser University; Fisheries and Oceans Canada","funders":"Arctic-Yukon-Kuskokwim Sustainable Salmon Initiative","keywords":"Overfishing; Population; Ecology; Population model; Vital rates; Stock (firearms); Population size; Ecosystem; Biology; Fishery; Population growth; Geography; Fishing; Demography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002245851,0.00009311022,0.0001344744,0.00001681775,0.001689699,0.00001331672,0.00022095,0.0000314294,0.002879176],"category_scores_gemma":[0.0000230219,0.00007756543,0.00002101972,0.0002326542,0.0002706629,0.00006804588,0.001906252,0.0001388723,0.0000737943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001639036,"about_ca_system_score_gemma":0.000003498006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004492471,"about_ca_topic_score_gemma":0.001793674,"domain_scores_codex":[0.9991406,0.00006683335,0.0001050551,0.0003722937,0.000111717,0.0002035043],"domain_scores_gemma":[0.9995564,0.0001602896,0.00003910347,0.0001677809,0.000003017059,0.0000734602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000244006,0.0003853044,0.9527557,0.000003122488,0.00001912763,0.000001959696,0.00009494679,0.0001307847,0.00003383581,0.001247347,0.04482657,0.0004768556],"study_design_scores_gemma":[0.0001806234,0.0001920236,0.8959961,2.474789e-7,0.00002021142,0.000001058564,0.0001840574,0.0000226604,0.00001558234,0.001875202,0.1014202,0.00009205476],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9715405,0.00001020489,0.00124301,0.01309268,0.00002936918,0.001251497,0.00004926186,0.0000787007,0.01270474],"genre_scores_gemma":[0.9943801,0.000006211361,0.0004116885,0.003287073,0.000007258817,0.001452647,0.00001501528,0.0000031898,0.0004368332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05675967,"threshold_uncertainty_score":0.9996099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01365508992618404,"score_gpt":0.1967133408555743,"score_spread":0.1830582509293902,"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."}}