{"id":"W4405465421","doi":"10.1089/forensic.2024.0013","title":"<i>Forensic Genomics</i> : 2024 in Review","year":2024,"lang":"en","type":"article","venue":"Forensic Genomics","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Genomics; Forensic science; Computational biology; Forensic genetics; Biology; Evolutionary biology; Data science; Computer science; Genetics; Genome; Gene; Microsatellite","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004862999,0.0002883327,0.0003237849,0.0001234769,0.00005442814,0.00006627192,0.0003274523,0.0001931962,0.0002491602],"category_scores_gemma":[0.00006060923,0.0002693381,0.0002173926,0.0003126581,0.000220208,0.000005338995,0.0002685919,0.0002894961,0.0008022161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000104493,"about_ca_system_score_gemma":0.0004075935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004946388,"about_ca_topic_score_gemma":0.0002044674,"domain_scores_codex":[0.9979912,0.00006016978,0.0004564077,0.0006977729,0.0002036178,0.0005908243],"domain_scores_gemma":[0.9990366,0.00002252494,0.00004417518,0.0006684593,0.00007616547,0.0001521009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008900888,0.00005530864,0.0002237511,0.001422888,0.0001778449,0.0001191533,0.0001713646,0.0003541264,0.09824421,0.001314321,0.7309905,0.1668375],"study_design_scores_gemma":[0.0003660233,0.0002388667,0.0002714197,0.0005129034,0.00004291282,0.0001717597,0.00006495746,0.0005528833,0.04223961,0.001330617,0.9537573,0.0004506873],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7252011,0.2383116,0.0007836723,0.002535691,0.00266681,0.001214827,0.0001266038,0.00004958271,0.02911012],"genre_scores_gemma":[0.7671702,0.1539843,0.00701741,0.007277364,0.002742368,0.0002344523,0.001315645,0.0003638861,0.05989433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2227668,"threshold_uncertainty_score":0.9999759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01301013424836133,"score_gpt":0.2746552665607716,"score_spread":0.2616451323124103,"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."}}