{"id":"W2897528226","doi":"10.1002/humu.23643","title":"Scaling resolution of variant classification differences in ClinVar between 41 clinical laboratories through an outlier approach","year":2018,"lang":"en","type":"article","venue":"Human Mutation","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children's Hospital of Eastern Ontario","funders":"National Human Genome Research Institute","keywords":"Outlier; Genetic variants; Identification (biology); Computational biology; Computer science; Biology; Artificial intelligence; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03897057,0.000974151,0.001873907,0.007080809,0.001738691,0.005165989,0.002275653,0.001400183,0.002500098],"category_scores_gemma":[0.1236291,0.0006166947,0.001359865,0.007850836,0.0009622634,0.001896897,0.006554096,0.001992979,0.001286449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001806476,"about_ca_system_score_gemma":0.003219087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005074497,"about_ca_topic_score_gemma":0.005569645,"domain_scores_codex":[0.9531133,0.01515583,0.007492987,0.01218272,0.0105082,0.001546951],"domain_scores_gemma":[0.8974817,0.03770493,0.01429075,0.0246814,0.02380172,0.002039507],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001965587,0.0006311513,0.4941066,0.0006085612,0.001200307,0.001240211,0.005868618,0.02038088,0.02085579,0.004633471,0.01584383,0.4326651],"study_design_scores_gemma":[0.0009133224,0.001879573,0.4251691,0.000550988,0.001121895,0.004069604,0.008738198,0.3936133,0.04497109,0.04176014,0.07636011,0.0008527182],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6859569,0.001055096,0.2895946,0.001600552,0.0004661219,0.001703927,0.006301279,0.007810225,0.005511344],"genre_scores_gemma":[0.6856183,0.0002409965,0.302105,0.0005035172,0.0001870505,0.000902944,0.008138432,0.0008781757,0.001425586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9610294,"threshold_uncertainty_score":0.2060986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1116306007184427,"score_gpt":0.3733427935820054,"score_spread":0.2617121928635627,"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."}}