{"id":"W4313308278","doi":"10.1089/forensic.2022.29015.editorial","title":"Highlighting the Forensic Impact of ISHI33","year":2022,"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":"Forensic science; Library science; Forensic identification; Forensic entomology; Download; Identification (biology); History; Computer science; World Wide Web; Archaeology; Biology; Ecology","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":[0.004440773,0.0006423772,0.0003192164,0.002406225,0.002460066,0.004284333,0.001260699,0.004140654,0.01499604],"category_scores_gemma":[0.008839005,0.000302571,0.0004776476,0.001049957,0.003363151,0.002404517,0.003962799,0.004260326,0.00354161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001739476,"about_ca_system_score_gemma":0.001996015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002422054,"about_ca_topic_score_gemma":0.00448068,"domain_scores_codex":[0.9985796,0.0004493575,0.00004622065,0.000148565,0.0005297973,0.000246452],"domain_scores_gemma":[0.9965633,0.001795764,0.0002213453,0.0003535867,0.0007917273,0.0002744452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004262846,0.0001070243,0.01404461,0.0008137421,0.00007232805,0.04163488,0.005092973,0.001003957,0.01599585,0.2193726,0.1454634,0.5559723],"study_design_scores_gemma":[0.00002964555,0.0001435451,0.00628648,0.001205275,0.0001072019,0.07462411,0.004843653,0.001353201,0.02022405,0.1087318,0.7823601,0.00009092019],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1086418,0.07397489,0.07149097,0.2645418,0.01444836,0.0001961988,0.0007419848,0.001130885,0.4648332],"genre_scores_gemma":[0.7709675,0.04825083,0.05269976,0.04218237,0.01099794,0.00008368508,0.0006085255,0.0006496882,0.0735597],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01499604,"threshold_uncertainty_score":0.05016679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01272944350664877,"score_gpt":0.268049530191629,"score_spread":0.2553200866849802,"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."}}