{"id":"W2118621341","doi":"10.1002/humu.20484","title":"PhenCode: connecting ENCODE data with mutations and phenotype","year":2007,"lang":"en","type":"article","venue":"Human Mutation","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Jewish General Hospital; Montreal Children's Hospital; Hospital for Sick Children","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; Ontario Genomics Institute; Cystic Fibrosis Canada; Genome Canada; National Institutes of Health; National Human Genome Research Institute; Cystic Fibrosis Foundation","keywords":"Biology; ENCODE; Genetics; Phenotype; Genome; 1000 Genomes Project; Gene; Computational biology; Single-nucleotide polymorphism; Genotype","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001335286,0.000065587,0.00004578938,0.00002623681,0.0001646958,0.00002862954,0.00008267081,0.000034464,0.00001194767],"category_scores_gemma":[0.00003454521,0.00006015617,0.000008615101,0.00003619464,0.00003870698,0.000006396735,0.00005139541,0.00002858094,0.000002820259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004701276,"about_ca_system_score_gemma":0.00002444785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000265097,"about_ca_topic_score_gemma":0.0004881469,"domain_scores_codex":[0.9995131,0.00001094078,0.00009574153,0.0002215451,0.00005477535,0.0001038842],"domain_scores_gemma":[0.9996278,0.00001120298,0.00005243891,0.000210998,0.00005056293,0.00004699207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002968895,0.0002475963,0.01769517,0.0001056307,0.0002296634,0.000121425,0.001889207,0.001036732,0.9026843,0.004583658,0.0007121858,0.07039753],"study_design_scores_gemma":[0.01103609,0.003379274,0.7195825,0.0001940843,0.0008807573,0.0009819453,0.02092274,0.007237806,0.1732185,0.009658063,0.04959659,0.003311647],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816284,0.0002561762,0.01660441,0.00002125313,0.0000271087,0.00008869737,0.00002927719,0.00001089566,0.001333771],"genre_scores_gemma":[0.9956589,0.000007550543,0.002456774,0.00006134376,0.00009633706,0.000001966863,0.001638951,0.0000125044,0.0000656488],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7294658,"threshold_uncertainty_score":0.2453097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02247637141668032,"score_gpt":0.2964828771600154,"score_spread":0.2740065057433351,"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."}}