{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001395547,0.00009029276,0.0001276231,0.000113144,0.0002457539,0.00001344573,0.000375799,0.000107041,0.00004723146],"category_scores_gemma":[0.0001985963,0.00008624791,0.00007420519,0.0003355423,0.0005844731,0.000004006897,0.0002740112,0.0001743831,0.0001090481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008378752,"about_ca_system_score_gemma":0.0005159295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006663999,"about_ca_topic_score_gemma":0.00001651186,"domain_scores_codex":[0.998018,0.0001866927,0.0003074498,0.0003943322,0.0005958119,0.0004977468],"domain_scores_gemma":[0.9986999,0.0000231681,0.00005700002,0.000652182,0.0004761314,0.00009163854],"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":[0.00003905742,0.00002781901,0.0009506295,0.0000296978,0.00002194757,0.000007963314,0.0004040212,0.0001678848,0.9961051,0.0001907146,0.001741951,0.0003132552],"study_design_scores_gemma":[0.0003739888,0.0004173788,0.04183757,0.000008408826,0.000003449104,0.00007468533,0.0005439955,0.0001307626,0.9218445,0.0003871376,0.03421359,0.0001644655],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912339,0.002875612,0.001785089,0.0001053016,0.00004915749,0.0002943788,0.00001792214,0.000005401497,0.003633174],"genre_scores_gemma":[0.9935467,0.001712139,0.0007943343,0.00003580087,0.000183692,0.00002657212,0.00005515276,0.00001987259,0.003625703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07426049,"threshold_uncertainty_score":0.3517088,"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."}}