{"id":"W3047010288","doi":"10.1158/1538-7445.pedca19-a58","title":"Abstract A58: Curation of pediatric cancer variants within the Clinical Genome Resource (ClinGen)","year":2020,"lang":"en","type":"article","venue":"Cancer Research","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pediatric cancer; Cancer; Medicine; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02277711,0.0009827685,0.0008880241,0.00494965,0.001820553,0.003923433,0.002940244,0.001529477,0.03161983],"category_scores_gemma":[0.03630387,0.000758137,0.0008502043,0.005132066,0.000656831,0.002254123,0.006073255,0.002100211,0.01546344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003281863,"about_ca_system_score_gemma":0.01833668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01497184,"about_ca_topic_score_gemma":0.01480702,"domain_scores_codex":[0.9886303,0.004170786,0.001357019,0.002064584,0.003068638,0.0007087384],"domain_scores_gemma":[0.9528349,0.01447796,0.004781794,0.007098252,0.01475084,0.006056315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005951536,0.0001288241,0.02784555,0.001156343,0.0001295521,0.0007471152,0.0006583498,0.00199241,0.004086267,0.005709768,0.8269233,0.1300273],"study_design_scores_gemma":[0.0004528449,0.0001629674,0.0339337,0.001031276,0.0001109219,0.001027897,0.0004476992,0.00442896,0.006422928,0.004043206,0.9478688,0.00006887064],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.06228487,0.007039804,0.2230885,0.04509789,0.0029532,0.009910276,0.4987456,0.0400514,0.1108285],"genre_scores_gemma":[0.08314985,0.001901816,0.3769321,0.008413623,0.001263204,0.005967629,0.4954473,0.007635299,0.01928905],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03161983,"threshold_uncertainty_score":0.1204583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1378485501055373,"score_gpt":0.4355653418474983,"score_spread":0.297716791741961,"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."}}