{"id":"W2810364471","doi":"10.1111/tan.13326","title":"Urdu speaking population from South India: Six extended haplotypes in linkage disequilibrium in Urdu Speaking Population","year":2018,"lang":"en","type":"article","venue":"HLA","topic":"Microbial infections and disease research","field":"Immunology and Microbiology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics; Université de Genève; Life Technologies Corporation","keywords":"Linkage disequilibrium; Haplotype; Population; Telugu; Urdu; Genetics; Allele frequency; Allele; Sanger sequencing; Biology; Demography; DNA sequencing; Gene; Sociology; Natural language processing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003040627,0.0001900155,0.0002827459,0.0004507029,0.0001661074,0.00005757841,0.0001501956,0.0003049599,0.001117326],"category_scores_gemma":[0.0001763979,0.0001880254,0.00008107798,0.0004219697,0.0001038709,0.0002757355,0.0001360028,0.000371847,0.0005987087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001565221,"about_ca_system_score_gemma":0.00004324474,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01293664,"about_ca_topic_score_gemma":0.006010925,"domain_scores_codex":[0.998287,0.0003047206,0.0004337155,0.0004429002,0.00006055248,0.0004710962],"domain_scores_gemma":[0.9993901,0.00008869777,0.000128897,0.0003008473,0.00005260264,0.00003881362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002611584,0.0002443457,0.8443078,0.00002696205,0.00004013514,0.00002518868,0.001812415,0.00003125989,0.1465662,0.0009063169,0.0001158344,0.005662425],"study_design_scores_gemma":[0.00116206,0.00006680463,0.9931725,0.0001470866,0.00001985327,0.00000655666,0.0001620862,0.0001658437,0.002737032,0.00129514,0.0008271462,0.0002378852],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972569,0.0005947176,0.0001096463,0.00007328139,0.0005652417,0.0003154221,0.0000550547,0.00008149928,0.0009482577],"genre_scores_gemma":[0.9986245,0.00001360428,0.0000550955,0.00005510712,0.0002262218,0.00001391055,0.0007729222,0.00002871362,0.0002099113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1488647,"threshold_uncertainty_score":0.9997958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01702026825526057,"score_gpt":0.2842469760385116,"score_spread":0.267226707783251,"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."}}