{"id":"W2084717763","doi":"10.1111/cge.12579","title":"The <scp>SickKids</scp> Genome Clinic: developing and evaluating a pediatric model for individualized genomic medicine","year":2015,"lang":"en","type":"review","venue":"Clinical Genetics","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Hospital for Sick Children","keywords":"Genome; Genomic medicine; Computational biology; Genetics; Medicine; Pediatrics; Biology; Gene","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004012684,0.0006128986,0.001619365,0.00008189468,0.0003390146,0.00008770726,0.0008784885,0.0008694316,0.000001708712],"category_scores_gemma":[0.003878768,0.0004156508,0.0006384227,0.0001457368,0.0003816452,0.000002045571,0.000802732,0.0003770084,0.00001855861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004078572,"about_ca_system_score_gemma":0.00241469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.883266e-7,"about_ca_topic_score_gemma":0.000004710389,"domain_scores_codex":[0.9954271,0.0004510338,0.002152244,0.001053647,0.0002947478,0.0006212345],"domain_scores_gemma":[0.9957151,0.001425988,0.001125869,0.0008813408,0.0004184993,0.0004332282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003147554,0.00009876299,0.0002155509,0.004140303,0.0008479502,0.000005220723,0.0001324732,0.00008729577,0.00002053538,0.00005984357,0.01216376,0.9821968],"study_design_scores_gemma":[0.001218039,0.0006065285,0.00008643115,0.0002329762,0.002330673,0.00002083429,0.00004984161,0.001011646,3.725419e-7,0.0008268636,0.9933649,0.0002508633],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.005967249,0.9894593,0.001772762,0.00003454042,0.0006467041,0.001709215,0.000264885,0.00001619818,0.000129144],"genre_scores_gemma":[0.00005454226,0.9846459,0.009524414,0.0003150064,0.002905098,0.0002438308,0.000931533,0.000148521,0.001231137],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.981946,"threshold_uncertainty_score":0.9998295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2562325552336077,"score_gpt":0.482919392998525,"score_spread":0.2266868377649173,"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."}}