{"id":"W4323568758","doi":"10.3390/d15030385","title":"Conservation Genetics of Lake Sturgeon (Acipenser fulvescens): Nuclear Phylogeography Drives Contemporary Patterns of Genetic Structure and Diversity","year":2023,"lang":"en","type":"article","venue":"Diversity","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Natural Resources and Forestry; Tetra Tech (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; West Virginia University; Ontario Ministry of Natural Resources and Forestry; Ministry of Natural Resources","keywords":"Ecology; Phylogeography; Acipenser; Beringia; Genetic structure; Glacial period; Genetic diversity; Biology; Lake sturgeon; Pleistocene; Conservation genetics; Range (aeronautics); Geography; Population; Sturgeon; Microsatellite; Paleontology; Phylogenetics; Fishery; Arctic; Demography; Allele","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006310187,0.00008636051,0.0001511021,0.00005658217,0.0003659652,0.000003004566,0.0001600481,0.00005699689,0.0002912111],"category_scores_gemma":[0.000009565138,0.00008899406,0.00004143697,0.0001605523,0.0003336162,0.00007732459,0.002884522,0.00005291579,0.00001010146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007938766,"about_ca_system_score_gemma":0.000001575688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003726923,"about_ca_topic_score_gemma":0.001816434,"domain_scores_codex":[0.9993854,0.00004053045,0.0001053273,0.0001905731,0.0001597079,0.0001184504],"domain_scores_gemma":[0.9996894,0.00003166189,0.0001095946,0.0001230258,0.00001428978,0.00003201481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002665838,0.00002677198,0.9912485,0.00004032245,0.00006620294,0.000007719177,0.001435197,0.00003610507,0.0002460833,0.00001793848,0.006686342,0.0001621237],"study_design_scores_gemma":[0.0003192148,0.00006953997,0.9978424,0.000005703729,0.00004174613,2.293977e-7,0.0006499572,0.00006125911,0.00009356526,0.0003066504,0.0005278214,0.0000819308],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988947,0.00001316354,0.00001023028,0.0001675576,0.00007450993,0.0001565848,0.0001579641,0.00002465203,0.0005006295],"genre_scores_gemma":[0.9994596,0.0001613619,0.00007943891,0.0002188309,0.000003947642,3.08595e-7,0.00001714339,0.000003067221,0.00005624754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006593847,"threshold_uncertainty_score":0.3629073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01386094156200318,"score_gpt":0.1864513532605739,"score_spread":0.1725904116985708,"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."}}