{"id":"W2321054149","doi":"10.18632/aging.100741","title":"Biomarkers and subtypes of cancer","year":2015,"lang":"en","type":"editorial","venue":"Aging","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"","keywords":"Cancer; Medicine; Computational biology; Biology; 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":[0.001896773,0.0007363794,0.001115673,0.00444504,0.0006199917,0.0033537,0.001452619,0.001729729,0.009391423],"category_scores_gemma":[0.01051192,0.0001972915,0.001065118,0.006489681,0.000972329,0.002205025,0.001528057,0.002065424,0.004379988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001654363,"about_ca_system_score_gemma":0.001326579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003502004,"about_ca_topic_score_gemma":0.002396513,"domain_scores_codex":[0.99783,0.0004407484,0.0002609003,0.000474358,0.0007215218,0.0002724414],"domain_scores_gemma":[0.995869,0.0008350443,0.001514825,0.0003774623,0.0009671305,0.0004364565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001102241,0.0001390043,0.4364774,0.002306125,0.0006401441,0.0006012829,0.0007616939,0.001578636,0.001822516,0.04605262,0.08050893,0.4280094],"study_design_scores_gemma":[0.0001104894,0.000428023,0.2999585,0.00273094,0.0006409016,0.009055953,0.001559695,0.002005186,0.001223868,0.123152,0.5590001,0.0001341854],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"editorial","genre_scores_codex":[0.207635,0.5101432,0.03522317,0.05003355,0.007584337,0.001156107,0.05202599,0.0009918516,0.1352069],"genre_scores_gemma":[0.7532244,0.1273185,0.02795813,0.00842113,0.006115069,0.0009979528,0.04699559,0.0003795323,0.02858965],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.009391423,"threshold_uncertainty_score":0.03141743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006444398061783754,"score_gpt":0.2731554148024029,"score_spread":0.2667110167406191,"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."}}