{"id":"W2795395475","doi":"10.1016/j.celrep.2018.03.077","title":"Molecular Characterization and Clinical Relevance of Metabolic Expression Subtypes in Human Cancers","year":2018,"lang":"en","type":"article","venue":"Cell Reports","topic":"Cancer, Hypoxia, and Metabolism","field":"Biochemistry, Genetics and Molecular Biology","cited_by":393,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Calgary","funders":"National Human Genome Research Institute; Invitae; Astex Pharmaceuticals; National Cancer Institute; National Institutes of Health; Boston Scientific Corporation; Array BioPharma; University of Texas System; University of Texas MD Anderson Cancer Center; Cancer Prevention and Research Institute of Texas; National Institute on Deafness and Other Communication Disorders; Bristol-Myers Squibb","keywords":"Computational biology; Biology; Gene expression; Clinical significance; Relevance (law); Cancer; Cancer research; Gene expression profiling; Gene; Genetics; Bioinformatics; Medicine; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0003304062,0.0001669943,0.0003852208,0.0007388294,0.0002070144,0.0005994944,0.0001751756,0.0001948575,0.0008939038],"category_scores_gemma":[0.0007090366,0.0001045318,0.000186567,0.001067301,0.0002379114,0.000247765,0.0003210776,0.0002795668,0.0002009858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000284996,"about_ca_system_score_gemma":0.00020466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007557793,"about_ca_topic_score_gemma":0.0013447,"domain_scores_codex":[0.9997744,0.00003838223,0.00002383366,0.00008323193,0.00004593156,0.00003424736],"domain_scores_gemma":[0.9996643,0.00009397533,0.0001095777,0.00006470907,0.00003757703,0.00002979672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007796033,0.00004201962,0.7893631,0.0001870723,0.0001962981,0.0002862428,0.0001376876,0.0008480096,0.1608032,0.001071872,0.0004808574,0.04580408],"study_design_scores_gemma":[0.00001746466,0.0001845956,0.9488279,0.00002329666,0.0001833671,0.002166267,0.0002455914,0.002053802,0.03783867,0.001888517,0.00655043,0.00002017768],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880913,0.004306542,0.003113054,0.0001329035,0.000009429974,0.00003088981,0.002541667,0.00004594064,0.001728152],"genre_scores_gemma":[0.9957494,0.0009394159,0.00122507,0.00003320511,0.00001013534,0.00002143725,0.001771338,0.00001281081,0.0002373106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008939038,"threshold_uncertainty_score":0.002990365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01009065260651491,"score_gpt":0.2817047996026925,"score_spread":0.2716141469961776,"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."}}