{"id":"W3200374960","doi":"10.1126/science.abg8289","title":"Protein-coding repeat polymorphisms strongly shape diverse human phenotypes","year":2021,"lang":"en","type":"article","venue":"Science","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":190,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Institute of Environmental Health Sciences; National Human Genome Research Institute; National Institute of Mental Health; National Heart, Lung, and Blood Institute; Wellcome Trust","keywords":"Phenotype; Biology; Genetics; Allele; Human genome; Biobank; Human genetics; Genetic variation; Coding region; Genome-wide association study; Genome; Single-nucleotide polymorphism; Gene; Genotype","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004088698,0.00008175958,0.00009391121,0.00003040538,0.0003757757,0.00003254797,0.0002465721,0.00006342794,0.0001075946],"category_scores_gemma":[0.0003565587,0.00007833529,0.00004773984,0.000196499,0.000260885,0.00000549893,0.0002503137,0.0000557383,0.00002264129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002399325,"about_ca_system_score_gemma":0.0001933292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001838082,"about_ca_topic_score_gemma":0.00003376505,"domain_scores_codex":[0.9989514,0.00004488357,0.0001377414,0.0004172346,0.0001412243,0.0003074862],"domain_scores_gemma":[0.9993902,0.000005724195,0.00006897983,0.0003161097,0.0001389695,0.00008005339],"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":[0.000001976224,0.00001715005,0.01264143,0.000001682257,0.00000578454,0.000003145628,0.00003085204,0.00003269752,0.984903,0.0006795765,0.0002231866,0.00145952],"study_design_scores_gemma":[0.0005047859,0.0002645126,0.2817138,0.00002132761,0.00002099227,0.0000279823,0.0006214876,0.0005657765,0.7032982,0.001063995,0.01147198,0.000425118],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952036,0.0002583642,0.0005996473,0.0002831462,0.0001324863,0.00007201477,0.000006218064,0.00001010778,0.003434479],"genre_scores_gemma":[0.9943048,0.00001359753,0.002931968,0.0001711886,0.0001315719,0.000008579475,0.00002058441,0.000005707964,0.002411997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2816048,"threshold_uncertainty_score":0.319442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02166390744730344,"score_gpt":0.2810720614373488,"score_spread":0.2594081539900453,"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."}}