{"id":"W4306750247","doi":"10.1111/eva.13489","title":"Re‐evaluating Coho salmon (<i>Oncorhynchus kisutch</i>) conservation units in Canada using genomic data","year":2022,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; University of Victoria; Université Laval","funders":"Genome British Columbia; Génome Québec; Genome Canada","keywords":"Biology; Oncorhynchus; Genetic diversity; Local adaptation; Genetic variation; Population; Evolutionary biology; Genetic structure; Microsatellite; Genotyping; Genotype; Fishery; Genetics; Allele; Gene; Demography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.002925814,0.0004622707,0.0005078541,0.002815444,0.001980532,0.001376877,0.001212043,0.0002634615,0.0005905607],"category_scores_gemma":[0.005872149,0.0001793179,0.0004260263,0.005347089,0.0007821021,0.0004673652,0.00115851,0.0004940592,0.0001001211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01261408,"about_ca_system_score_gemma":0.01680964,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9749256,"about_ca_topic_score_gemma":0.9920853,"domain_scores_codex":[0.9978926,0.0003007322,0.0001367393,0.0003749849,0.0007516438,0.0005433931],"domain_scores_gemma":[0.9944622,0.0005621752,0.0007627423,0.0002978427,0.003438506,0.0004765224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000113506,0.00002131877,0.9741499,0.0001051197,0.0002384984,0.0001041238,0.001403667,0.001431093,0.003301557,0.0003244643,0.001869939,0.01693686],"study_design_scores_gemma":[0.000005717744,0.0000191474,0.9928603,0.00004312711,0.00005969555,0.00001812018,0.002491862,0.001699965,0.000537094,0.00006303724,0.002191884,0.000009934543],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908637,0.00060693,0.002679934,0.0002498215,0.00002022569,0.0001259342,0.003689434,0.00005484628,0.001709089],"genre_scores_gemma":[0.9899435,0.0002394607,0.005021908,0.0001353133,0.000006437928,0.00005704599,0.004062111,0.00002403127,0.00051016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02507436,"threshold_uncertainty_score":0.09152192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05754712943148713,"score_gpt":0.2723843580424401,"score_spread":0.214837228610953,"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."}}