{"id":"W2992856559","doi":"10.1534/g3.119.400747","title":"Genome Assembly and Analysis of the North American Mountain Goat (<i>Oreamnos americanus</i>) Reveals Species-Level Responses to Extreme Environments","year":2019,"lang":"en","type":"article","venue":"G3 Genes Genomes Genetics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"Mitacs; Université de Lille; Compute Canada; Alaska Department of Fish and Game; Agence Nationale de la Recherche; Natural Sciences and Engineering Research Council of Canada; Massachusetts Department of Fish and Game","keywords":"Biology; Demographic history; Evolutionary biology; Phylogeography; Population; Population genomics; Genome; Range (aeronautics); Ancient DNA; Phylogenetic tree; Ecology; Lineage (genetic); Effective population size; Genomics; Genetics; Demography; Genetic variation; Gene","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0001692887,0.0002862579,0.000180838,0.0005807802,0.0004446903,0.0004036066,0.0002084885,0.0002648172,0.001015752],"category_scores_gemma":[0.0004025789,0.0001469958,0.0004785205,0.0004805727,0.0001698855,0.0002713106,0.0002733083,0.0003351468,0.0003990976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002657069,"about_ca_system_score_gemma":0.000500649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005006036,"about_ca_topic_score_gemma":0.01269351,"domain_scores_codex":[0.9999179,0.000008662851,0.000005326233,0.00003271662,0.00002084825,0.00001452406],"domain_scores_gemma":[0.9998691,0.00003224698,0.00003212956,0.00001372309,0.00003047439,0.00002215744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002852571,0.00005660328,0.01781301,0.0001798855,0.00005130356,0.000467037,0.0005864326,0.0008392807,0.9635636,0.0004445638,0.0009018726,0.01481116],"study_design_scores_gemma":[0.00003965454,0.0005702056,0.7180963,0.00009413072,0.0002792785,0.001514948,0.0009212394,0.01002522,0.2237803,0.0007020388,0.04391418,0.00006243463],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9819053,0.0005783323,0.009140865,0.0001564669,0.00002807984,0.00003981985,0.006458332,0.0002134806,0.001479143],"genre_scores_gemma":[0.8905222,0.0007906698,0.04532151,0.000163971,0.00003173928,0.0001181518,0.05795595,0.000257896,0.004837916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005006036,"threshold_uncertainty_score":0.009953797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0214131916064431,"score_gpt":0.233366264872158,"score_spread":0.2119530732657149,"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."}}