{"id":"W4212972218","doi":"10.1002/humu.24354","title":"Genomics4RD: An integrated platform to share Canadian deep-phenotype and multiomic data for international rare disease gene discovery.","year":2022,"lang":"en","type":"article","venue":"PubMed","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network; Newborn Screening Ontario; McGill University; Children's Hospital of Eastern Ontario; Hospital for Sick Children; University of Ottawa","funders":"Canadian Institutes of Health Research","keywords":"Standardization; Data collection; Data science; Data access; Computer science; Data sharing; World Wide Web; Database; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001078116,0.0001265768,0.0000870388,0.0000847971,0.0002124576,0.0001089384,0.0005965605,0.0000330348,0.00002489947],"category_scores_gemma":[0.0001678138,0.0001313186,0.00003528703,0.00004934419,0.00002012152,0.00001907011,0.0005006478,0.00004877427,0.000001093649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00010127,"about_ca_system_score_gemma":0.000233726,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002751143,"about_ca_topic_score_gemma":0.02166406,"domain_scores_codex":[0.9989765,0.0000145939,0.0001378931,0.0004918822,0.00007875454,0.0003003201],"domain_scores_gemma":[0.9988424,0.000005766714,0.00004018942,0.0004918998,0.00008811228,0.0005316222],"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":[0.01429094,0.001768454,0.07565634,0.0002618828,0.002540476,0.0003881394,0.001219386,0.01740817,0.0464946,0.002948727,0.1041926,0.7328303],"study_design_scores_gemma":[0.002087571,0.000167129,0.2749378,0.000003585467,0.0001202204,0.00002251004,0.0008570002,0.007555269,0.0009327152,0.0002777934,0.7121717,0.00086665],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9675695,0.0004447092,0.0005570479,0.0005127708,0.0005143485,0.0009162715,0.02942713,0.000009064307,0.00004916608],"genre_scores_gemma":[0.9603999,0.00003427412,0.0005080242,0.001269262,0.000252843,0.001038872,0.0361199,0.00003022132,0.0003466564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7319636,"threshold_uncertainty_score":0.996188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02470455690855912,"score_gpt":0.2359403151682506,"score_spread":0.2112357582596914,"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."}}