{"id":"W4406864540","doi":"10.1016/j.fsigen.2025.103232","title":"X-chromosomal STRs: Metapopulations and mutation rates","year":2025,"lang":"en","type":"article","venue":"Forensic Science International Genetics","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cytodiagnostics (Canada)","funders":"European Regional Development Fund; Programa Operacional Temático Factores de Competitividade; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Ministério da Ciência, Tecnologia e Inovação; Fundação para a Ciência e a Tecnologia; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Metapopulation; Biology; Mutation; Mutation rate; Genetics; Evolutionary biology; Gene; Demography","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":[0.003466779,0.0003793267,0.0007133693,0.00351634,0.0003456171,0.001342531,0.000552951,0.0005406984,0.001002985],"category_scores_gemma":[0.004281564,0.0002587551,0.0006933715,0.002621437,0.000568455,0.000906849,0.0006060333,0.0005142819,0.0002315497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005318089,"about_ca_system_score_gemma":0.0002386971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001379721,"about_ca_topic_score_gemma":0.001175771,"domain_scores_codex":[0.9984822,0.0004981029,0.0001239017,0.0005340683,0.0002588421,0.0001028675],"domain_scores_gemma":[0.9968582,0.001586199,0.0008299846,0.000424464,0.0001693386,0.0001318611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004484097,0.000102648,0.8816485,0.0002170244,0.001408328,0.0006673433,0.001228692,0.02577538,0.03214543,0.005336306,0.0001879401,0.05083397],"study_design_scores_gemma":[0.00003715349,0.0002409189,0.9332152,0.00005443062,0.0003369674,0.001703255,0.0005944198,0.04832286,0.004710581,0.008890494,0.001798163,0.00009552544],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869044,0.001299877,0.01024081,0.00005009177,0.000006791603,0.00002838178,0.0005226113,0.00006137384,0.00088549],"genre_scores_gemma":[0.9955036,0.0003426617,0.003518796,0.000007628899,0.000008803104,0.000020105,0.0003531081,0.0000152148,0.0002300965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00351634,"threshold_uncertainty_score":0.01833433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01494044182359816,"score_gpt":0.3492088303191046,"score_spread":0.3342683884955064,"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."}}