{"id":"W2126379430","doi":"10.1101/gr.124354.111","title":"Translating cancer ‘omics’ to improved outcomes: Figure 1.","year":2012,"lang":"en","type":"article","venue":"Genome Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":117,"is_retracted":false,"has_abstract":true,"ca_institutions":"Occupational Cancer Research Centre; University of British Columbia","funders":"Congressionally Directed Medical Research Programs; National Institute of Dental and Craniofacial Research; National Human Genome Research Institute; National Cancer Institute; National Institutes of Health; Canadian Institutes of Health Research; Canary Foundation; U.S. Department of Defense","keywords":"Omics; Biology; Genomics; Computational biology; Cancer; Annotation; Translational research; Genome; Bioinformatics; Genetics; Biotechnology; Gene","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":[0.01179539,0.0017923,0.001105499,0.002396462,0.001110647,0.008663736,0.001697519,0.00315351,0.0103927],"category_scores_gemma":[0.01382489,0.0005923575,0.0009889101,0.0022944,0.005183771,0.00777983,0.00367878,0.004666232,0.005571291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002510015,"about_ca_system_score_gemma":0.004023883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00272614,"about_ca_topic_score_gemma":0.002552115,"domain_scores_codex":[0.9962392,0.001593192,0.0002491547,0.0004331996,0.001329201,0.0001561133],"domain_scores_gemma":[0.9927538,0.003690556,0.000574642,0.0008277015,0.00160901,0.0005442215],"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":[0.0003220733,0.0001725856,0.0102674,0.003512878,0.0003924387,0.0005646725,0.001040176,0.002063797,0.005249255,0.271566,0.2322384,0.4726104],"study_design_scores_gemma":[0.00009029204,0.0002448162,0.01044723,0.001990522,0.0002320817,0.0009490282,0.0008568663,0.003164716,0.003526434,0.6433722,0.3350008,0.0001249639],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.009650434,0.07635716,0.2012236,0.6104456,0.01220116,0.0006938101,0.00586546,0.004098658,0.07946418],"genre_scores_gemma":[0.1515831,0.1266809,0.5036047,0.1742234,0.01433719,0.001256583,0.004284304,0.0009529632,0.0230769],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01179539,"threshold_uncertainty_score":0.06238073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06185142402885312,"score_gpt":0.3884896562938341,"score_spread":0.326638232264981,"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."}}