{"id":"W4395053828","doi":"10.1016/j.fsigen.2024.103053","title":"Ethical considerations for Forensic Genetic Frequency databases: First Report conception and development","year":2024,"lang":"en","type":"article","venue":"Forensic Science International Genetics","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University and Génome Québec Innovation Centre","funders":"","keywords":"Forensic science; Database; Engineering ethics; Computer science; Data science; Biology; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.1825856,0.001323673,0.001241846,0.00351129,0.004185017,0.01872781,0.004596537,0.01189182,0.007886207],"category_scores_gemma":[0.3288883,0.001773949,0.001500221,0.002007402,0.007099113,0.008108896,0.01267872,0.01126573,0.006241031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008253636,"about_ca_system_score_gemma":0.05090418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00255001,"about_ca_topic_score_gemma":0.001888642,"domain_scores_codex":[0.7918798,0.1023497,0.01685309,0.006985678,0.0760013,0.005930396],"domain_scores_gemma":[0.6543688,0.1304016,0.02167049,0.03165349,0.1393718,0.02253382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001929729,0.0003057517,0.004095599,0.002155989,0.00005250101,0.001966628,0.0174011,0.0006521008,0.002527056,0.2487041,0.5186512,0.2032948],"study_design_scores_gemma":[0.00006171885,0.000196805,0.001550697,0.003689282,0.00003092664,0.002656589,0.005486141,0.000861905,0.002974456,0.03129492,0.951072,0.0001245842],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01185789,0.01970332,0.2219727,0.5757231,0.03626971,0.02990762,0.005286054,0.001208454,0.09807124],"genre_scores_gemma":[0.09746072,0.02404858,0.5711747,0.1153087,0.02437249,0.06149046,0.005808419,0.001373876,0.09896208],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9881082,"threshold_uncertainty_score":0.9656163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05621233013882287,"score_gpt":0.3652090835581309,"score_spread":0.308996753419308,"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."}}