{"id":"W4392574918","doi":"10.1093/molbev/msae038","title":"Genomic Analyses Capture the Human-Induced Demographic Collapse and Recovery in a Wide-Ranging Cervid","year":2024,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"Natural Sciences and Engineering Research Council of Canada; Trent University","keywords":"Biology; Demographic history; Last Glacial Maximum; Range (aeronautics); Coalescent theory; Effective population size; Ecology; Population; Vicariance; Climate change; Glacial period; Phylogeography; Genetic variation; Demography; Phylogenetics; Paleontology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002545002,0.00007588107,0.00007653255,0.00007163423,0.0001642391,0.00001533476,0.00005180318,0.0001370799,0.00003222319],"category_scores_gemma":[0.00002603136,0.00005751149,0.00002642401,0.0002397564,0.0001636572,0.00006199272,0.00006012653,0.0001267352,0.00001166511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004890547,"about_ca_system_score_gemma":0.00000903117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006266944,"about_ca_topic_score_gemma":0.001177086,"domain_scores_codex":[0.9993679,0.0001430322,0.000101293,0.0002243327,0.00002743913,0.000136013],"domain_scores_gemma":[0.9998194,0.00005658869,0.00002101355,0.00008105482,0.000002466452,0.00001949801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009094054,0.000006418124,0.8519739,0.000005055833,0.00001999153,0.000009827194,0.0001109616,0.0001539835,0.1461577,0.000994499,0.0001061115,0.0004525422],"study_design_scores_gemma":[0.0001040806,0.00004203019,0.9847745,0.00001050696,0.0000278368,0.00001618486,0.00006115087,0.001403752,0.0001963528,0.01314832,0.0001392671,0.00007595894],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944691,0.002323282,0.001402125,0.001361766,0.00008368952,0.0001161557,0.000001647557,0.00001873234,0.0002234769],"genre_scores_gemma":[0.9992579,0.00007017265,0.00004788179,0.0005457408,0.00001124526,0.00001772241,0.000009248744,0.000004143271,0.00003597934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1459613,"threshold_uncertainty_score":0.234525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0122169018113454,"score_gpt":0.2631336644077027,"score_spread":0.2509167625963573,"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."}}