{"id":"W2611574484","doi":"10.1016/j.ajhg.2017.04.003","title":"International Cooperation to Enable the Diagnosis of All Rare Genetic Diseases","year":2017,"lang":"en","type":"article","venue":"The American Journal of Human Genetics","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":453,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of Toronto; University of British Columbia; McGill University; Children's Hospital of Eastern Ontario; University of Ottawa","funders":"National Human Genome Research Institute; National Heart, Lung, and Blood Institute; Medical Research Council; Ontario Genomics Institute; Canadian Institutes of Health Research; Genome Canada; Ontario Genomics; Wellcome Trust; European Commission; Johns Hopkins University; University of Washington","keywords":"Computer science; Computational biology; Biology","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":[0.0001183041,0.00009550394,0.0001456002,0.00003066227,0.0002433138,0.00008674577,0.0009978171,0.00001535854,0.00002531931],"category_scores_gemma":[0.00009995536,0.00005694702,0.0001230406,0.000025374,0.0002946436,0.000003579207,0.000201674,0.00005447173,0.000002094228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009624018,"about_ca_system_score_gemma":0.00006590601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000222519,"about_ca_topic_score_gemma":0.00001504657,"domain_scores_codex":[0.9992863,0.00006268889,0.0002620429,0.0001038103,0.0001649277,0.000120222],"domain_scores_gemma":[0.9985674,0.00001780436,0.0005581819,0.0005065984,0.0002642493,0.00008577745],"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":[0.0008528997,0.0006418841,0.2212225,0.00002721056,0.001468214,0.00006325717,0.001382768,0.01564492,0.6392498,0.0002165933,0.03719643,0.08203349],"study_design_scores_gemma":[0.001246771,0.004655523,0.694944,0.00007427717,0.0005600666,0.0001891935,0.001372457,0.0001439154,0.1651275,0.0007141271,0.1304672,0.0005050066],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971203,0.00106087,0.0001521391,0.001215597,0.0001688496,0.00009750482,0.00004257943,9.768888e-7,0.0001412427],"genre_scores_gemma":[0.9971156,0.001380533,0.0003098216,0.0005521675,0.000525372,0.000007046152,0.000009275639,0.00001433825,0.00008584747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4741223,"threshold_uncertainty_score":0.2322232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01485170619201797,"score_gpt":0.2918985219165635,"score_spread":0.2770468157245455,"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."}}