{"id":"W3188520353","doi":"10.1016/j.isci.2021.102925","title":"A panoramic view of proteomics and multiomics in precision health","year":2021,"lang":"en","type":"review","venue":"iScience","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"National Institute of General Medical Sciences; Canadian Institutes of Health Research; National Institutes of Health; Chan Zuckerberg Initiative; Simons Foundation Autism Research Initiative; Silicon Valley Community Foundation; Simons Foundation","keywords":"Disease; Computational biology; Genomics; Data science; Genome; Proteomics; Precision medicine; Biology; Bioinformatics; Computer science; Genetics; Medicine; Gene; Pathology","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":[0.002930165,0.001409791,0.001475538,0.003755028,0.0005764933,0.002375028,0.001413885,0.003437049,0.003536573],"category_scores_gemma":[0.002414803,0.0004386421,0.0007430111,0.003686749,0.002901313,0.004988614,0.002069277,0.005842948,0.002452312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002084732,"about_ca_system_score_gemma":0.002258814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001160637,"about_ca_topic_score_gemma":0.001557569,"domain_scores_codex":[0.9992894,0.000223644,0.00006791412,0.000103608,0.0002576578,0.00005770902],"domain_scores_gemma":[0.9978153,0.001424342,0.0001087447,0.00009275751,0.0003911812,0.000167652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000868841,0.00008895145,0.0002369468,0.0142507,0.0001593949,0.0003460701,0.0002253518,0.0006615182,0.00182372,0.09307207,0.07090872,0.8181397],"study_design_scores_gemma":[0.000009957177,0.00005688998,0.0004093825,0.0035239,0.0000415573,0.0007206373,0.0000859258,0.0001429288,0.0003625807,0.0246377,0.9699812,0.00002740072],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00005124831,0.9945031,0.0009837667,0.002085585,0.0007824837,0.000005468942,0.0000138761,0.0000177561,0.001556666],"genre_scores_gemma":[0.0007672121,0.9949596,0.0009969365,0.001376894,0.00113297,0.00001245592,0.00002403498,0.00000657437,0.0007233522],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003755028,"threshold_uncertainty_score":0.01549637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02756177795267659,"score_gpt":0.329750698536146,"score_spread":0.3021889205834694,"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."}}