{"id":"W2894590458","doi":"10.1016/j.fsigen.2018.10.002","title":"Repeatedly washed semen stains: Optimal screening and sampling strategies for DNA analysis","year":2018,"lang":"en","type":"article","venue":"Forensic Science International Genetics","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Golder Associates (Canada); Nicolet Chartrand Knoll (Canada); Université Laval; Concordia University","funders":"","keywords":"Semen; Sampling (signal processing); Stain; Sperm; Chromatography; Biology; Andrology; Chemistry; Staining; Medicine; Computer science; Genetics","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":[],"consensus_categories":[],"category_scores_codex":[0.0005805446,0.0001404133,0.0001293227,0.0002433747,0.0002759623,0.0002221735,0.0004547889,0.00007212924,0.00002450352],"category_scores_gemma":[0.0001668477,0.0001302573,0.0000864419,0.0004184114,0.001300433,0.00001643969,0.0002975813,0.00005230952,0.000002378844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002094978,"about_ca_system_score_gemma":0.000189088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002702837,"about_ca_topic_score_gemma":0.00009766805,"domain_scores_codex":[0.9983212,0.0000151564,0.0002444838,0.0005695388,0.0004669043,0.000382719],"domain_scores_gemma":[0.998568,0.00002339802,0.0000798125,0.0003079368,0.0008952856,0.0001255834],"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":[0.0004349864,0.00006889317,0.02223691,0.00002149242,0.001102815,0.000003610662,0.0009947732,0.01620723,0.8276171,0.002636581,0.001599486,0.1270761],"study_design_scores_gemma":[0.001623925,0.002192504,0.04791414,0.00003156484,0.0002570344,0.00004669921,0.003083877,0.306412,0.6039612,0.004153843,0.029487,0.0008362571],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7060781,0.0001126788,0.2926373,0.0001401889,0.0001794508,0.0001444539,0.00002697494,0.000008188468,0.0006725874],"genre_scores_gemma":[0.8952515,0.00005837109,0.1036351,0.0001391558,0.0004224491,0.00001629705,0.00009414635,0.0000119884,0.0003710384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2902048,"threshold_uncertainty_score":0.5311739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03503487187972182,"score_gpt":0.3584415282133026,"score_spread":0.3234066563335808,"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."}}