{"id":"W2122955674","doi":"10.1194/jlr.d045963","title":"LipidSeq: a next-generation clinical resequencing panel for monogenic dyslipidemias","year":2014,"lang":"en","type":"article","venue":"Journal of Lipid Research","topic":"Lipoproteins and Cardiovascular Health","field":"Medicine","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research","keywords":"Sanger sequencing; Exome sequencing; Dyslipidemia; Concordance; Genetics; Computational biology; Exome; DNA sequencing; Biology; Bioinformatics; Medicine; Mutation; Gene; Disease; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002308197,0.0007152859,0.0004992787,0.001396716,0.0005726579,0.0007187288,0.0006097284,0.0008234395,0.003090899],"category_scores_gemma":[0.002218311,0.0004291666,0.0004715286,0.0006251208,0.0002726213,0.0003494049,0.0008816288,0.0007979398,0.001766498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00044293,"about_ca_system_score_gemma":0.0006666636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001139411,"about_ca_topic_score_gemma":0.001878609,"domain_scores_codex":[0.9986933,0.0003375146,0.0001481908,0.0003497466,0.0003760153,0.00009528742],"domain_scores_gemma":[0.9989799,0.0003688521,0.0001262838,0.00009346996,0.0003115731,0.0001200157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.008972389,0.0007091128,0.2405422,0.0004998402,0.0005743543,0.005474922,0.001197978,0.008277899,0.4814083,0.001496305,0.0268075,0.2240392],"study_design_scores_gemma":[0.001800441,0.005676916,0.5058982,0.000196063,0.0009811203,0.0180828,0.0004553739,0.0374091,0.3056795,0.002719695,0.1206548,0.0004458946],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8606907,0.002237219,0.08948351,0.001494929,0.000168559,0.002013003,0.02771145,0.002645422,0.01355518],"genre_scores_gemma":[0.8287851,0.001087992,0.1142375,0.004193886,0.0001863086,0.002621673,0.04108644,0.0005324819,0.007268623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003090899,"threshold_uncertainty_score":0.01220703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5409540244862475,"score_gpt":0.4939419183266643,"score_spread":0.04701210615958323,"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."}}