{"id":"W2071278424","doi":"10.1002/path.4542","title":"Categorization of cancer through genomic complexity could guide research and management strategies","year":2015,"lang":"en","type":"review","venue":"The Journal of Pathology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; University of British Columbia","funders":"Terry Fox Research Institute; KWF Kankerbestrijding; National Institute for Health and Care Research; BC Cancer Agency; University College London; Cancer Research UK","keywords":"Categorization; Context (archaeology); Disease; Cancer; Genomic information; Genomics; Personalized medicine; Bioinformatics; Precision medicine; Computational biology; Medicine; Data science; Genome; Computer science; Biology; Genetics; Pathology; Artificial intelligence; Internal medicine; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001364903,0.0001551211,0.0006148192,0.00008025576,0.00005892303,0.0000178987,0.0003846795,0.0001911254,0.000007236432],"category_scores_gemma":[0.00003855049,0.0001030296,0.0000911453,0.00009796281,0.000436312,0.000003557672,0.0002920998,0.0002624456,0.000001354522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006887619,"about_ca_system_score_gemma":0.0006007854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009807563,"about_ca_topic_score_gemma":0.0001471828,"domain_scores_codex":[0.9986082,0.0003241637,0.000574372,0.0001440536,0.000166803,0.0001823622],"domain_scores_gemma":[0.9985477,0.00006402301,0.000613823,0.0002932292,0.0004371667,0.00004410885],"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":[0.0007766741,0.0005407513,0.0001311111,0.022162,0.00307317,0.000470055,0.001875978,0.00116949,0.008958285,0.04717316,0.08444235,0.829227],"study_design_scores_gemma":[0.0002731851,0.0005100946,0.00003651651,0.0004086953,0.0004285352,0.0003526153,0.000282576,0.000001442902,0.00007618484,0.004346978,0.9931741,0.0001091261],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001871178,0.995767,0.0007273207,0.00006612975,0.0002703527,0.0002752504,0.00007542287,8.502579e-7,0.0009464908],"genre_scores_gemma":[0.0007196876,0.9982133,0.000473695,0.00003028832,0.0003549905,0.000009117748,0.00003631478,0.00002225716,0.0001403672],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9087317,"threshold_uncertainty_score":0.4201425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1941727316067084,"score_gpt":0.461844008922398,"score_spread":0.2676712773156895,"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."}}