{"id":"W4390278310","doi":"10.1016/j.fsigen.2023.103005","title":"Identifying distant relatives using benchtop-scale sequencing","year":2023,"lang":"en","type":"article","venue":"Forensic Science International Genetics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"DNA sequencing; Kinship; Forensic genetics; Computational biology; Genome; Whole genome sequencing; DNA sequencer; Genetics; Biology; Microsatellite; DNA; Gene","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":[0.0007105058,0.0004137844,0.0006550377,0.0009519496,0.0009186425,0.001273755,0.0005491592,0.0009896797,0.006523937],"category_scores_gemma":[0.001194083,0.0002983937,0.0005289173,0.001058551,0.000373222,0.000610865,0.0006712491,0.0008255816,0.003809496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002722932,"about_ca_system_score_gemma":0.0004399513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002123957,"about_ca_topic_score_gemma":0.008620808,"domain_scores_codex":[0.9995709,0.00005869306,0.00001938614,0.0002024404,0.00009983275,0.00004862811],"domain_scores_gemma":[0.9990195,0.0003316322,0.0001197386,0.0002129484,0.0001883607,0.0001278063],"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":[0.0002964508,0.0001468763,0.02875728,0.0001534188,0.0001249345,0.0005031079,0.0006612141,0.0006789755,0.9125709,0.0009827166,0.0009439249,0.05418025],"study_design_scores_gemma":[0.0001619291,0.001241977,0.4461793,0.0002341656,0.0009164084,0.00488632,0.003870038,0.02689257,0.3606998,0.01069698,0.144111,0.0001096735],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8590569,0.001012219,0.1130293,0.0002035041,0.000145155,0.0002795474,0.008261681,0.0009803072,0.01703147],"genre_scores_gemma":[0.7569587,0.0007200642,0.2027617,0.0007354891,0.0001081854,0.0002013325,0.02293796,0.0004140375,0.01516254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006523937,"threshold_uncertainty_score":0.02182472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05222758442771221,"score_gpt":0.3216777104017532,"score_spread":0.269450125974041,"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."}}