{"id":"W2269102739","doi":"10.1373/clinchem.2015.247858","title":"Proteogenomics: Opportunities and Caveats","year":2016,"lang":"en","type":"article","venue":"Clinical Chemistry","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Mount Sinai Hospital; University of Toronto","funders":"Prostate Cancer Canada","keywords":"Proteogenomics; Computational biology; Biology; Proteome; Proteomics; Ensembl; Genomics; Pseudogene; Genome; Identification (biology); Druggability; Human proteome project; Exome; Exome sequencing; DNA sequencing; Genetics; Gene; Phenotype","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":[0.1067244,0.002406042,0.003017869,0.004161309,0.00306139,0.00771259,0.007256338,0.005300462,0.007953424],"category_scores_gemma":[0.1734941,0.0008442831,0.002616512,0.003733016,0.01733451,0.01703565,0.007908709,0.0203558,0.00490411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00285151,"about_ca_system_score_gemma":0.005323477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005618038,"about_ca_topic_score_gemma":0.006558614,"domain_scores_codex":[0.958266,0.020199,0.0044071,0.004059937,0.01227413,0.0007937593],"domain_scores_gemma":[0.7967827,0.1541662,0.005281742,0.01851456,0.02273808,0.002516625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005322474,0.000211319,0.006444144,0.005190912,0.0005710265,0.001809078,0.002478424,0.001727675,0.0009678885,0.4414572,0.3008426,0.2377675],"study_design_scores_gemma":[0.0000944379,0.0001234169,0.003750184,0.002804179,0.0001535011,0.004305598,0.001487701,0.003016456,0.000737346,0.5921587,0.3911757,0.0001927533],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.005209964,0.1447485,0.08066083,0.7129542,0.02737678,0.0003690672,0.001276149,0.001297856,0.02610657],"genre_scores_gemma":[0.105964,0.1199372,0.1867348,0.4990586,0.06155965,0.002718706,0.00110028,0.001464239,0.02146268],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.1067244,"threshold_uncertainty_score":0.5644195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08803035209775073,"score_gpt":0.3526974424539431,"score_spread":0.2646670903561924,"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."}}