{"id":"W2954313009","doi":"10.1101/gr.245522.118","title":"Estimation of allele-specific fitness effects across human protein-coding sequences and implications for disease","year":2019,"lang":"en","type":"article","venue":"Genome Research","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; National Institutes of Health; University of Toronto","keywords":"Biology; Genetics; Exome sequencing; Exome; Genomics; Population; Population genomics; Balancing selection; Allele frequency; Genome; Human genome; Single-nucleotide polymorphism; Computational biology; Allele; 1000 Genomes Project; Gene; Mutation; Genotype","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002150533,0.000620753,0.0006969722,0.001495125,0.0003821788,0.0007378528,0.0004710965,0.00066863,0.0006508162],"category_scores_gemma":[0.008772098,0.0002224777,0.0005018555,0.0007792788,0.0008725463,0.0006586657,0.0008617579,0.0008861434,0.0000922753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003392963,"about_ca_system_score_gemma":0.0002967307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002825886,"about_ca_topic_score_gemma":0.002465351,"domain_scores_codex":[0.9994227,0.0002647677,0.00002476558,0.0001994099,0.00005602725,0.00003235047],"domain_scores_gemma":[0.9954928,0.003905336,0.000265939,0.0001872107,0.00006947193,0.00007919565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003456839,0.00008586015,0.3201957,0.0001090432,0.0005456664,0.0004801484,0.0002865669,0.5888524,0.02650085,0.01012706,0.0004445863,0.05202648],"study_design_scores_gemma":[0.00003206001,0.00007879745,0.09930228,0.00001819641,0.0001067725,0.000306596,0.0001258851,0.8603861,0.003345004,0.03567858,0.0005723161,0.00004739789],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8476765,0.0005451369,0.1504592,0.0002899906,0.000009989434,0.00001366193,0.0003730277,0.0001585058,0.0004739968],"genre_scores_gemma":[0.9900684,0.0001981649,0.009199752,0.00006012603,0.00001191799,0.00001363664,0.0002899661,0.00002077621,0.0001372253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002825886,"threshold_uncertainty_score":0.01137328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04007239187349591,"score_gpt":0.3893156482938051,"score_spread":0.3492432564203092,"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."}}