{"id":"W3097027093","doi":"10.1139/cjfas-2020-0152","title":"Parentage-based tagging improves escapement estimates for ESA-listed adult Chinook salmon and steelhead in the Snake River basin","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":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bonneville Power Administration; National Marine Fisheries Service; California Department of Fish and Wildlife; U.S. Fish and Wildlife Service; Washington Department of Fish and Wildlife; Idaho Department of Fish and Game; Columbia River Inter-Tribal Fish Commission; Massachusetts Department of Fish and Game","keywords":"Chinook wind; Escapement; Hatchery; Oncorhynchus; Fishery; Endangered species; Biology; Broodstock; Spawn (biology); Rainbow trout; Fish hatchery; Fish <Actinopterygii>; Habitat; Ecology; Aquaculture; Fish farming","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":[0.001883461,0.0003485059,0.0003318495,0.0008037091,0.000379461,0.0005902137,0.000380746,0.00027109,0.0005597976],"category_scores_gemma":[0.00321966,0.0002478269,0.0003692037,0.0004599316,0.0002998607,0.0005156285,0.0006395656,0.000224055,0.0002366903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005369329,"about_ca_system_score_gemma":0.000477152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04318896,"about_ca_topic_score_gemma":0.1271696,"domain_scores_codex":[0.9993016,0.0001538439,0.00005871856,0.0002951484,0.0001275317,0.00006308239],"domain_scores_gemma":[0.9986921,0.0002806165,0.0003498172,0.0001274462,0.0004441787,0.0001059062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001217484,0.00001621287,0.9821106,0.00001080344,0.00009164609,0.00003796511,0.0002823122,0.0009407516,0.006934399,0.00002511635,0.00009443926,0.009334102],"study_design_scores_gemma":[0.000005093528,0.00009055027,0.9914852,0.00000530995,0.00004547564,0.00003185107,0.0001762391,0.007186168,0.0008040784,0.00003091782,0.000129762,0.00000941551],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986533,0.00002311469,0.000968996,0.000009720381,0.000002598,0.000003930521,0.00007525615,0.00001844717,0.0002444698],"genre_scores_gemma":[0.9979462,0.00001531866,0.001420938,0.00001501621,0.000001698626,0.000004099823,0.0003278521,0.00000985082,0.000259095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04318896,"threshold_uncertainty_score":0.08587515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01784575990577021,"score_gpt":0.2157684882187708,"score_spread":0.1979227283130006,"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."}}