{"id":"W4289782615","doi":"10.1371/journal.pone.0271767","title":"Identifying signatures of natural selection in Indian populations","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Amgen (Canada); University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Natural Sciences and Engineering Research Council of Canada; Mitacs; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Coalescent theory; Evolutionary biology; Biology; Natural selection; Outlier; Population; False positive paradox; Selection (genetic algorithm); Computational biology; Genetics; Computer science; Gene; Phylogenetics; Artificial intelligence; Demography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001067619,0.00003932527,0.0000636843,0.00007888695,0.00006533573,0.000004754723,0.00008296087,0.0000313942,0.00006611916],"category_scores_gemma":[0.00004438478,0.0000431013,0.00002365423,0.0001670185,0.00002339453,0.000001399544,0.00009163411,0.0001366771,0.000001109486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001447789,"about_ca_system_score_gemma":0.00003409119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007644181,"about_ca_topic_score_gemma":0.0002243812,"domain_scores_codex":[0.9994259,0.00005255653,0.00009976281,0.0001211143,0.0001931446,0.0001075575],"domain_scores_gemma":[0.9998397,0.000003855127,0.00002997696,0.00007443008,0.00003451109,0.00001753557],"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":[0.00003573537,0.0002011427,0.02368185,0.00002091024,0.00003174023,0.000001180245,0.0001115223,0.0002803633,0.9748796,0.00008761462,0.0002509872,0.0004173127],"study_design_scores_gemma":[0.0004708277,0.0003260901,0.1403296,0.0000200846,0.00001571273,0.000003756112,0.0003417963,0.0007260821,0.8567383,0.0007006005,0.0001928012,0.0001343337],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989317,0.0006363982,0.00001734872,0.00007149277,0.00002765807,0.0001100475,0.000007355005,0.000002896411,0.0001950938],"genre_scores_gemma":[0.9980506,0.0000178563,0.0009811763,0.00003239594,0.0000403486,0.00002371973,0.00009000484,0.000006458568,0.0007573977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1181413,"threshold_uncertainty_score":0.175762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04690325572475359,"score_gpt":0.2923096491203324,"score_spread":0.2454063933955788,"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."}}