{"id":"W4296492642","doi":"10.1089/forensic.2022.29013.editorial","title":"<i>Forensic Genomics</i> : A New Era","year":2022,"lang":"en","type":"article","venue":"Forensic Genomics","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Genomics; Forensic science; Identification (biology); Forensic identification; Forensic entomology; Library science; Data science; Computer science; Biology; History; Genome; Archaeology; Genetics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000170508,0.0002649002,0.0002440697,0.00004370321,0.0008344595,0.00002887035,0.0005591767,0.00004841737,0.005115025],"category_scores_gemma":[0.00001034001,0.0003042447,0.000149087,0.0002049168,0.0003663064,0.0001106775,0.002605141,0.0003278375,0.002508261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001804643,"about_ca_system_score_gemma":0.00002122837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007446882,"about_ca_topic_score_gemma":0.0001447119,"domain_scores_codex":[0.9981777,0.00004462194,0.0002569376,0.0005611956,0.0004244758,0.0005350367],"domain_scores_gemma":[0.9991474,0.00003310704,0.0001305185,0.0004918415,0.000002524834,0.0001946769],"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":[0.0001391146,0.000215452,0.1620527,0.000009335226,0.000150998,0.00009814277,0.006099563,0.02955963,0.01842682,0.0003066556,0.7323405,0.05060117],"study_design_scores_gemma":[0.001128315,0.0003241331,0.124714,0.000002256975,0.00008895604,0.0001164228,0.001999039,0.0004247239,0.004198568,0.003583424,0.8626388,0.0007812538],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988528,0.0001800622,0.00007932116,0.000881442,0.0006810126,0.0003755249,0.0001258478,0.00007932773,0.009069477],"genre_scores_gemma":[0.9334944,0.000183084,0.04598391,0.006105463,0.0002946907,0.00005233673,0.0001608606,0.0001005584,0.01362464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1302984,"threshold_uncertainty_score":0.999941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01132204225087808,"score_gpt":0.1784099106507154,"score_spread":0.1670878683998374,"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."}}