{"id":"W4409900189","doi":"10.1111/mec.17772","title":"Leveraging Whole Genomes, Mitochondrial <scp>DNA</scp> and Haploblocks to Decipher Complex Demographic Histories: An Example From a Broadly Admixed Arctic Fish","year":2025,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Université du Québec à Rimouski; Université Laval; Center for Northern Studies","funders":"Université de Montpellier; Genome Canada; Aarhus Universitet","keywords":"Biology; Evolutionary biology; Phylogeography; Mitochondrial DNA; Genome; Lineage (genetic); Haplotype; Demographic history; Genomics; Population; Arctic; Genetics; Genetic variation; Phylogenetics; Ecology; Gene; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005272736,0.0002175851,0.0002405582,0.00105473,0.00111811,0.0007919499,0.0002413616,0.0003081144,0.0005717068],"category_scores_gemma":[0.0008101279,0.0001283383,0.0002088707,0.001821708,0.00065528,0.0002655443,0.0004954009,0.0004517365,0.0001619341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001238714,"about_ca_system_score_gemma":0.001556226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2659698,"about_ca_topic_score_gemma":0.5945506,"domain_scores_codex":[0.9998684,0.00001697468,0.000004904557,0.00004530469,0.00003074243,0.00003363093],"domain_scores_gemma":[0.9995075,0.0001134189,0.00007015907,0.00005751161,0.0001563495,0.00009496234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004715487,0.00003941419,0.6484319,0.0004015872,0.0004933225,0.001902888,0.008509838,0.003763168,0.2389657,0.002777894,0.001295726,0.092947],"study_design_scores_gemma":[0.00000518246,0.00004768356,0.9736506,0.00008567756,0.0001612602,0.0007061244,0.002745955,0.002368021,0.005134233,0.001324533,0.01372555,0.0000450566],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882547,0.001474914,0.006462128,0.0002759675,0.000008323567,0.00001220382,0.001287908,0.00005529755,0.002168462],"genre_scores_gemma":[0.9794631,0.001386408,0.01660586,0.0002030278,0.000009889385,0.000007055334,0.001284471,0.0000446925,0.0009954325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2659698,"threshold_uncertainty_score":0.5288433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01571822105421969,"score_gpt":0.2287394114636727,"score_spread":0.2130211904094531,"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."}}