{"id":"W2015503410","doi":"10.1038/nmeth.2049","title":"Managing deep data in genome browsers","year":2012,"lang":"en","type":"article","venue":"Nature Methods","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Michael Smith Health Research BC; Research Canada; Canadian Institutes of Health Research","funders":"","keywords":"Genome; Computational biology; Computer science; Biology; Data science; World Wide Web; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001003837,0.0001195528,0.0001297095,0.00004496323,0.00004114072,0.000009798885,0.000391147,0.0002188284,0.000009771784],"category_scores_gemma":[0.0001543512,0.000111204,0.00003397973,0.00009946762,0.00003141863,0.000001344624,0.0005013209,0.0002123922,0.000003496597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001032351,"about_ca_system_score_gemma":0.00001365507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009769054,"about_ca_topic_score_gemma":0.00002288805,"domain_scores_codex":[0.9990686,0.0001486585,0.0001283137,0.000286491,0.00006374707,0.0003042467],"domain_scores_gemma":[0.9991784,0.00002804272,0.00003825188,0.0006732728,0.00002050151,0.0000615372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003166654,0.0000495465,0.02580645,0.00002222519,0.00009446032,0.000001672076,0.0002511258,0.00003778221,0.9080948,0.0003035632,0.0003653947,0.06494132],"study_design_scores_gemma":[0.0005407056,0.00005742244,0.2073648,0.000006650635,0.00004451414,0.00002009826,0.0003357427,0.0001843264,0.04939288,0.001067627,0.7405273,0.0004579384],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7866554,0.1610254,0.03524847,0.0005772646,0.001593426,0.0003180426,0.00003839289,0.000009547362,0.01453403],"genre_scores_gemma":[0.7906758,0.0007862842,0.2072891,0.0005437908,0.0004498582,0.000006852799,0.00008064707,0.00001842118,0.0001492416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8587019,"threshold_uncertainty_score":0.4534766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02881439647261967,"score_gpt":0.3704781492535578,"score_spread":0.3416637527809381,"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."}}