{"id":"W4307563137","doi":"10.1111/eva.13495","title":"Demographic history and conservation genomics of caribou (<i>Rangifer tarandus</i>) in Québec","year":2022,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Gouvernement du Québec; Université Laval; Ministère des Ressources naturelles et des Forêts; Trent University","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada; Genome Canada","keywords":"Biology; Genomics; Conservation biology; Diversity (politics); Genetic diversity; Ecology; Population genomics; Evolutionary biology; Genome; Genetics; Population; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006821348,0.00005327926,0.00006145499,0.00006938672,0.0001115268,0.000001246639,0.00008532823,0.00004251954,0.00008691554],"category_scores_gemma":[0.000005376266,0.0000684924,0.00002991258,0.0001071388,0.00008618669,0.000002802614,0.00008332492,0.00006421086,8.534141e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006790966,"about_ca_system_score_gemma":0.0001752704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001731919,"about_ca_topic_score_gemma":0.0009014416,"domain_scores_codex":[0.9995394,0.00003830699,0.0001281447,0.0001548587,0.00007357621,0.00006568111],"domain_scores_gemma":[0.9997222,0.000008820614,0.00006091985,0.0001479031,0.000035336,0.00002478153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002085311,0.0002462138,0.7849963,0.00004855371,0.00008140767,0.000001017167,0.0006985835,0.01188419,0.1363323,0.01606859,0.04725731,0.002177028],"study_design_scores_gemma":[0.0003069385,0.00003207524,0.3253544,7.654774e-7,0.00001189581,0.00001072193,0.0001270794,0.000256508,0.0001580309,0.0003862146,0.6732739,0.00008147352],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908392,0.00545652,0.002126816,0.0007011661,0.00004995273,0.0002838432,0.0001595015,0.000006636523,0.0003763264],"genre_scores_gemma":[0.9979427,0.00009388419,0.0007701233,0.0002551248,0.00002533119,0.0001057479,0.0004774007,0.000004951461,0.0003246683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6260166,"threshold_uncertainty_score":0.2793039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008253587534146177,"score_gpt":0.192269943721244,"score_spread":0.1840163561870979,"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."}}