{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002296613,0.00009168276,0.0001881153,0.00003565114,0.00003037277,0.000006276718,0.00004860129,0.0001180768,0.000009268571],"category_scores_gemma":[0.00007321328,0.00008963255,0.00005013619,0.00006454775,0.0001288472,0.000005033385,0.00005482876,0.00005565358,4.444346e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004303867,"about_ca_system_score_gemma":0.00008116625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000511669,"about_ca_topic_score_gemma":0.0000356014,"domain_scores_codex":[0.9990443,0.0000460423,0.0003728057,0.0003214966,0.00008686468,0.0001284983],"domain_scores_gemma":[0.999306,0.000003898421,0.0002501283,0.0003063813,0.00007748225,0.00005613613],"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":[0.00002903327,0.00002751094,0.01670277,0.00001357814,0.000007503048,0.000004746684,0.00003294298,0.000002192998,0.9800323,0.00001206688,0.0001379912,0.002997346],"study_design_scores_gemma":[0.0002058516,0.00005996615,0.05689217,0.00001805301,0.00001440134,0.000006895653,0.000006044552,0.000004710826,0.7684575,0.00001960279,0.1742331,0.00008171889],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992926,0.005053628,0.0003728306,0.000009644005,0.0008942825,0.0001260622,0.000003479179,0.000004321198,0.0006097492],"genre_scores_gemma":[0.9949744,0.00356082,0.000170617,0.00007167614,0.0007134072,0.000007606815,0.00005622251,0.00001383405,0.0004313558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2115748,"threshold_uncertainty_score":0.3655109,"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."}}