{"id":"W2100196176","doi":"10.1038/ncomms2140","title":"The genetic prehistory of southern Africa","year":2012,"lang":"en","type":"article","venue":"Nature Communications","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":372,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Institute of Environmental Health Sciences; National Institute of General Medical Sciences; National Human Genome Research Institute; Japan Society for the Promotion of Science; Max-Planck-Gesellschaft; Deutsche Forschungsgemeinschaft; European Science Foundation; National Institutes of Health; National Science Foundation","keywords":"Prehistory; Bantu languages; Evolutionary biology; Human migration; Genetic genealogy; Out of africa; Population; Geography; Genetic variation; Genetic data; Phylogeography; 1000 Genomes Project; Biology; Ethnology; Single-nucleotide polymorphism; History; Phylogenetics; Demography; Archaeology; Genetics; Genotype; 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":[0.0002637616,0.0002056016,0.0001756089,0.001177803,0.0007865072,0.0004909081,0.0001462913,0.0001841055,0.001907216],"category_scores_gemma":[0.001141538,0.0001360222,0.00008895648,0.001780638,0.0007615043,0.0003716675,0.0005888675,0.0002443695,0.0001307702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005180943,"about_ca_system_score_gemma":0.0003777681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01220256,"about_ca_topic_score_gemma":0.02122145,"domain_scores_codex":[0.9998291,0.00004088672,0.000009054068,0.00004621039,0.00002741185,0.00004729699],"domain_scores_gemma":[0.9996599,0.00008639148,0.0001275647,0.00002783611,0.00005083311,0.00004747919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003751281,0.0000313222,0.8485386,0.0001799487,0.0001296427,0.00187803,0.02069623,0.0003570992,0.05148052,0.002533433,0.0002536057,0.07354634],"study_design_scores_gemma":[0.000004388466,0.00003230643,0.9941502,0.00003352514,0.00001577097,0.0004190041,0.001632303,0.0000546544,0.0004267266,0.0004629559,0.002761556,0.000006573829],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975431,0.0007503644,0.000110729,0.00007724839,0.00000281094,0.000004799832,0.00008514302,0.000001904945,0.001423861],"genre_scores_gemma":[0.9989002,0.0006213963,0.0001678885,0.00002243583,0.000005193423,0.000003704902,0.00008437427,0.000001454657,0.0001933698],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01220256,"threshold_uncertainty_score":0.02426308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01982144640601143,"score_gpt":0.2993879089746777,"score_spread":0.2795664625686663,"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."}}