{"id":"W4225282363","doi":"10.1002/wfs2.1459","title":"Evolution of single‐nucleotide polymorphism use in forensic genetics","year":2022,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Forensic Science","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Forensic identification; Genetics; Single-nucleotide polymorphism; Forensic science; Biology; Computational biology; SNP; DNA profiling; Microsatellite; Forensic genetics; Typing; Primer (cosmetics); Genetic marker; Evolutionary biology; DNA; Gene; Genotype; Allele","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001526075,0.0002451243,0.0004012802,0.0003542362,0.0003548242,0.00003624505,0.0009146628,0.00006121909,0.00006694511],"category_scores_gemma":[0.0001992946,0.0002257542,0.0002073563,0.001220264,0.001586615,0.00002753943,0.003064116,0.0002267471,0.00001430735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000242098,"about_ca_system_score_gemma":0.0002844813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005948906,"about_ca_topic_score_gemma":0.0002357735,"domain_scores_codex":[0.9969792,0.0002114184,0.0007334988,0.0007808366,0.0006791875,0.0006158179],"domain_scores_gemma":[0.9984017,0.00002927576,0.0002725537,0.0009797014,0.0001633379,0.0001534122],"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":[0.0002519946,0.0003128957,0.0234574,0.00008078264,0.00001841507,0.00002383784,0.0006301433,0.0009415348,0.8923002,0.0004143692,0.01156554,0.07000288],"study_design_scores_gemma":[0.005443727,0.0176975,0.1685121,0.001831992,0.0001937814,0.001401039,0.006329393,0.01242843,0.5862983,0.01456924,0.181462,0.003832472],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984408,0.01257504,0.0005195162,0.0001736605,0.000709269,0.0006761954,0.00003453182,0.000008995128,0.000894842],"genre_scores_gemma":[0.9959632,0.0007783246,0.002417519,0.0001117041,0.0001279473,0.00008600702,0.00004224949,0.00002560953,0.0004474332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3060019,"threshold_uncertainty_score":0.9205989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03721963161351286,"score_gpt":0.3143912417677139,"score_spread":0.277171610154201,"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."}}