{"id":"W1800480040","doi":"10.1016/j.fsigen.2015.08.003","title":"52 additional reference population samples for the 55 AISNP panel","year":2015,"lang":"en","type":"article","venue":"Forensic Science International Genetics","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Oak Ridge Institute for Science and Education; Office of Justice Programs; National Natural Science Foundation of China; U.S. Department of Energy; Federal Bureau of Investigation; National Institute of Justice; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu; U.S. Department of Justice; National Science Foundation","keywords":"Population; Massive parallel sequencing; Allele frequency; Single-nucleotide polymorphism; Biology; Inference; Allele; Genetics; Computational biology; Statistics; Computer science; DNA sequencing; Genotype; Mathematics; Gene; Demography; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002044411,0.001193348,0.001072496,0.004263732,0.002088606,0.0012881,0.001362819,0.001305673,0.04554497],"category_scores_gemma":[0.005084141,0.0006406335,0.001074287,0.002901963,0.0004281815,0.0003441986,0.00139436,0.001004709,0.01341726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007178833,"about_ca_system_score_gemma":0.0009583155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02558221,"about_ca_topic_score_gemma":0.03195775,"domain_scores_codex":[0.9975394,0.0003718111,0.0003208527,0.001016846,0.0004472874,0.0003038253],"domain_scores_gemma":[0.9988319,0.000202224,0.00007067475,0.0004252423,0.0003781588,0.00009171434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004165002,0.002309477,0.2648734,0.001419209,0.001559121,0.008676988,0.007960509,0.003046572,0.1885501,0.006113845,0.1460759,0.3652499],"study_design_scores_gemma":[0.0009651973,0.001065594,0.4868934,0.00068958,0.001922807,0.008628568,0.002073419,0.002136322,0.04498597,0.003359194,0.4470598,0.0002200528],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6617771,0.003787204,0.04324188,0.001135613,0.001140055,0.00268154,0.195203,0.001773222,0.08926049],"genre_scores_gemma":[0.5472211,0.001497421,0.0420099,0.002522265,0.0001840553,0.002252888,0.3521239,0.0008887149,0.05129987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04554497,"threshold_uncertainty_score":0.1523631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1034116105127397,"score_gpt":0.3093091825997479,"score_spread":0.2058975720870082,"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."}}