{"id":"W2115233244","doi":"10.1111/j.1752-4571.2010.00156.x","title":"The emergence of human‐evolutionary medical genomics","year":2010,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Population genomics; Genomics; Evolutionary biology; Natural selection; Population; Genetics; Human evolutionary genetics; Disease; Human genetics; Selection (genetic algorithm); Population genetics; Lineage (genetic); Balancing selection; Genetic variation; Phylogenetics; Genome; Gene; Machine learning; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008613124,0.0004067999,0.0008858636,0.001454647,0.001114898,0.003200166,0.0008450144,0.00228196,0.002576197],"category_scores_gemma":[0.007578844,0.0003496828,0.0004380533,0.001229831,0.01194849,0.00431064,0.003088768,0.004220294,0.0003424829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001967343,"about_ca_system_score_gemma":0.001959662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001207843,"about_ca_topic_score_gemma":0.00103868,"domain_scores_codex":[0.9973451,0.001673603,0.00008922153,0.000389459,0.0003638097,0.0001387743],"domain_scores_gemma":[0.9918352,0.006260934,0.0003309628,0.0006665267,0.0005495524,0.0003568181],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004671494,0.00003526706,0.004344884,0.0003802143,0.00006115013,0.0002821277,0.001289704,0.001106241,0.001239528,0.8939249,0.00408105,0.09320828],"study_design_scores_gemma":[0.00002239927,0.000144178,0.01005601,0.0003390786,0.00003731412,0.001346083,0.001166838,0.002757741,0.0009783733,0.7377108,0.2453821,0.00005918408],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.05145794,0.1874022,0.4188026,0.2335594,0.003365075,0.000211191,0.0004459374,0.0003585101,0.1043972],"genre_scores_gemma":[0.6491857,0.1006425,0.1996401,0.03254672,0.00816605,0.0003447944,0.0003267656,0.0001767787,0.008970721],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.008613124,"threshold_uncertainty_score":0.04555112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007724641313241634,"score_gpt":0.277636836026499,"score_spread":0.2699121947132574,"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."}}