{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01626611,0.000326874,0.000343874,0.003407689,0.0008592085,0.003158539,0.001196196,0.001256945,0.002299679],"category_scores_gemma":[0.0223491,0.0002728923,0.0003537098,0.003459238,0.002406456,0.001868122,0.001634234,0.001440574,0.0008216474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001871903,"about_ca_system_score_gemma":0.001380294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002443751,"about_ca_topic_score_gemma":0.003660999,"domain_scores_codex":[0.9877486,0.006908206,0.0005982535,0.001791375,0.002610542,0.0003429984],"domain_scores_gemma":[0.9759588,0.0127772,0.002858931,0.001686388,0.005925023,0.0007936205],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002220907,0.0001473585,0.1706372,0.000451865,0.0002096773,0.000665044,0.0058142,0.001210441,0.0144939,0.05549011,0.004076527,0.7465817],"study_design_scores_gemma":[0.00003395311,0.0007854028,0.3855409,0.003595365,0.000371216,0.01283341,0.009752898,0.0179275,0.04143985,0.05633249,0.4711501,0.0002369117],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.7608778,0.05445,0.07124218,0.01528324,0.000855311,0.00021866,0.000622352,0.0002409804,0.09620942],"genre_scores_gemma":[0.9451315,0.01323464,0.03381843,0.001335966,0.0002387635,0.00006192307,0.0001923354,0.0001190649,0.005867446],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9837339,"threshold_uncertainty_score":0.0860244,"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."}}