{"id":"W4404692548","doi":"10.1016/j.ajhg.2024.10.022","title":"Demographic history and genetic variation of the Armenian population","year":2024,"lang":"en","type":"article","venue":"The American Journal of Human Genetics","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity College","funders":"European Social Fund; Tartu Ülikool; Ministry of Education and Science","keywords":"Armenian; Demographic history; Population; Population bottleneck; Geography; Genetic variation; Gene pool; Demography; Biology; Genetic diversity; Evolutionary biology; Genetics; Ancient history; History; Allele; Microsatellite; Gene","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":[0.0002644375,0.0002287995,0.000265415,0.001106151,0.0003795835,0.000533145,0.0002313324,0.0002048586,0.002072683],"category_scores_gemma":[0.001090401,0.0001547221,0.000230751,0.001674281,0.0001663679,0.0002240465,0.0004957039,0.0002798831,0.0003057623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003724463,"about_ca_system_score_gemma":0.0002228084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01408891,"about_ca_topic_score_gemma":0.01419009,"domain_scores_codex":[0.9998477,0.00002942713,0.00001208239,0.00007759481,0.00001388116,0.00001947297],"domain_scores_gemma":[0.9998645,0.00003234619,0.00003478795,0.00003884139,0.00001602915,0.0000135555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004480405,0.00005317379,0.9041598,0.0001720066,0.0006614926,0.0008961085,0.00223845,0.006574252,0.009985641,0.002510133,0.00532358,0.06697738],"study_design_scores_gemma":[0.0000171619,0.00002915609,0.9838747,0.00005917719,0.0001016647,0.0003415889,0.0003167341,0.001797222,0.0003898955,0.0006713662,0.01238354,0.00001787141],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821419,0.0003611243,0.001097993,0.0000726675,0.000006815204,0.00001337938,0.01497113,0.00002057307,0.001314432],"genre_scores_gemma":[0.9689595,0.0005119844,0.002381209,0.00005411216,0.000009105704,0.00006414259,0.02728811,0.0000112814,0.00072053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01408891,"threshold_uncertainty_score":0.02801377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01121881562101445,"score_gpt":0.265672483178022,"score_spread":0.2544536675570075,"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."}}