{"id":"W2104414368","doi":"10.1080/00085030.2006.10757144","title":"General Guidelines for Categorization and Interpretation of Mixed STR DNA Profiles","year":2006,"lang":"en","type":"article","venue":"Canadian Society of Forensic Science Journal","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interpretation (philosophy); Categorization; Sorting; Sample (material); Computer science; Natural language processing; Artificial intelligence; Algorithm; Chemistry; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005569811,0.00006411798,0.00009582345,0.00006200889,0.0001579244,0.00002914203,0.0001395029,0.00005983286,0.000003305852],"category_scores_gemma":[0.0001272366,0.00005606249,0.00008058484,0.0001441903,0.0007456685,0.00001075303,0.00002080876,0.00003884927,7.643095e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003276766,"about_ca_system_score_gemma":0.0009241021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002070225,"about_ca_topic_score_gemma":0.004254044,"domain_scores_codex":[0.9991829,0.00000932477,0.0002457939,0.0001454822,0.0001968822,0.0002195764],"domain_scores_gemma":[0.9986167,0.00000613991,0.0001250821,0.00009263938,0.001026053,0.0001333708],"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":[0.00002458673,0.000009420093,0.006247208,0.00004094784,0.00002604595,2.845758e-7,0.0002098943,0.0007392323,0.8311952,0.0007736919,0.08999577,0.07073765],"study_design_scores_gemma":[0.0005168315,0.000342815,0.01749244,0.00003338433,0.00001565076,0.0000446874,0.0008007588,0.01974806,0.9555582,0.002707488,0.002605638,0.0001339864],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874625,0.0003949269,0.01106156,0.000662176,0.0001490753,0.0001250489,0.00002614663,8.886233e-7,0.0001177132],"genre_scores_gemma":[0.9466833,0.00008424773,0.05263377,0.0001019821,0.0002351073,0.000002778889,0.00003304567,0.00000567141,0.0002200435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.124363,"threshold_uncertainty_score":0.3129574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02103035640249113,"score_gpt":0.3037521023505141,"score_spread":0.282721745948023,"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."}}