{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006225135,0.0004409599,0.0004092584,0.001052008,0.0003554183,0.0006870138,0.0002609969,0.0005998753,0.002798442],"category_scores_gemma":[0.002180873,0.0002168786,0.0002881149,0.001343995,0.0008401253,0.0002957402,0.0007819366,0.0005986614,0.000480406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002073725,"about_ca_system_score_gemma":0.0001296727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001665643,"about_ca_topic_score_gemma":0.002517423,"domain_scores_codex":[0.999,0.0003401956,0.00006383545,0.0003676931,0.0001661406,0.00006217026],"domain_scores_gemma":[0.9988802,0.0004116741,0.0004492383,0.000121193,0.00006605966,0.00007150502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004495393,0.00004946321,0.9636126,0.00005664666,0.000317761,0.0006046971,0.0003301477,0.000543159,0.01638699,0.0007581206,0.0006967376,0.01619412],"study_design_scores_gemma":[0.000005117013,0.00003787782,0.9969813,0.000008238519,0.00003944587,0.0006156603,0.00007477198,0.0003161418,0.0005630368,0.0007951235,0.0005544256,0.000008921863],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920874,0.001438699,0.001898607,0.0003550638,0.00002045303,0.00001678252,0.001061576,0.00005366787,0.0030677],"genre_scores_gemma":[0.9976138,0.0005203526,0.0007976225,0.0001180653,0.00002101702,0.000007897076,0.0003906717,0.00002114934,0.0005094539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002798442,"threshold_uncertainty_score":0.009361684,"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."}}