{"id":"W2167546325","doi":"10.1101/gr.076091.108","title":"Identification of ancient remains through genomic sequencing","year":2008,"lang":"en","type":"article","venue":"Genome Research","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Lawrence Berkeley National Laboratory; Los Alamos National Laboratory; Biological and Environmental Research; Social Sciences and Humanities Research Council of Canada; Office of Science; National Institutes of Health; Lawrence Livermore National Laboratory; National Human Genome Research Institute; U.S. Department of Energy","keywords":"Biology; Ancient DNA; DNA sequencing; Deep sequencing; Genetics; Illumina dye sequencing; genomic DNA; Polymerase chain reaction; Genomics; Phylogenetic tree; Multiple displacement amplification; Massive parallel sequencing; Computational biology; DNA; Evolutionary biology; Genome; DNA extraction; Gene; Population","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":[0.0005290143,0.0003009154,0.0004459205,0.002353573,0.0003276527,0.0006738626,0.0004896058,0.0005344332,0.001143404],"category_scores_gemma":[0.001763785,0.000183848,0.0003157498,0.001376893,0.0003681858,0.0003857231,0.0005738772,0.0006153229,0.0009957511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002134424,"about_ca_system_score_gemma":0.000400188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001048916,"about_ca_topic_score_gemma":0.002363164,"domain_scores_codex":[0.9996547,0.0000471881,0.00002950586,0.0001268935,0.0001105426,0.00003117575],"domain_scores_gemma":[0.999266,0.0002064759,0.0001297674,0.0001364877,0.0002173398,0.00004392174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001152326,0.000038149,0.008836663,0.0003705596,0.00005297768,0.0008286877,0.0005852231,0.001165591,0.8984211,0.003904379,0.0004761012,0.08520531],"study_design_scores_gemma":[0.00006054581,0.0005839725,0.1517146,0.0003368875,0.0005654246,0.006768237,0.001336507,0.02038847,0.6321339,0.01237014,0.1736504,0.00009100139],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5852472,0.004111981,0.3900837,0.0003154578,0.0001274363,0.0002980714,0.008816613,0.001143671,0.009855736],"genre_scores_gemma":[0.593178,0.004821976,0.3792229,0.0003170165,0.00008617051,0.0002083491,0.0148382,0.0002729183,0.007054411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002353573,"threshold_uncertainty_score":0.003825068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09981368815561636,"score_gpt":0.3692142112480754,"score_spread":0.269400523092459,"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."}}