{"id":"W2769352072","doi":"10.1101/203018","title":"Paleo-Eskimo genetic legacy across North America","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Ostravská Univerzita v Ostravě; National Institute of General Medical Sciences; Wenner-Gren Foundation; Howard Hughes Medical Institute; Smithsonian Institution; National Institutes of Health; National Science Foundation","keywords":"Ancient DNA; Haplotype; Arctic; Geography; Phylogenetic tree; Allele frequency; Evolutionary biology; Ethnology; Genealogy; Allele; Archaeology; Biology; History; Demography; Ecology; Population; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003516613,0.0001253179,0.000213742,0.0009035527,0.0007194764,0.0006172033,0.0002057848,0.0001461591,0.00145335],"category_scores_gemma":[0.000576692,0.00006974302,0.0001070836,0.001439135,0.0003993983,0.0002499502,0.0006099087,0.0002011288,0.0001176245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003733713,"about_ca_system_score_gemma":0.0004328844,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04282834,"about_ca_topic_score_gemma":0.07999332,"domain_scores_codex":[0.9998637,0.00002620807,0.000005336077,0.00006176092,0.00002574372,0.00001710098],"domain_scores_gemma":[0.9997088,0.00006965101,0.00007294019,0.00003743263,0.00005784888,0.00005331057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001505288,0.00004268217,0.9376062,0.00005880901,0.0001989428,0.0003221432,0.003862697,0.001371757,0.008471615,0.001015476,0.0005544684,0.04634459],"study_design_scores_gemma":[0.000002743231,0.00001065124,0.9965922,0.00002520125,0.00002440517,0.00007555313,0.0007684292,0.0005812732,0.0002072497,0.0004459388,0.001261325,0.000004960717],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998282,0.0003013317,0.0002015047,0.0000669037,0.000002247919,0.000002186989,0.0002161129,0.000006416581,0.0009212803],"genre_scores_gemma":[0.9990256,0.0002953157,0.0001997109,0.00001964533,0.000003958403,0.000003277643,0.0002465145,0.00000303808,0.0002029516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9571717,"threshold_uncertainty_score":0.08515811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01526464251582512,"score_gpt":0.2667592530977164,"score_spread":0.2514946105818913,"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."}}