{"id":"W3131728774","doi":"10.1200/cci.20.00108","title":"OncoTree: A Cancer Classification System for Precision Oncology","year":2021,"lang":"en","type":"article","venue":"JCO Clinical Cancer Informatics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":150,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"National Institute of Neurological Disorders and Stroke; National Cancer Institute","keywords":"Cancer; Medicine; Precision medicine; SNOMED CT; Clinical Oncology; Oncology; Genomics; Internal medicine; Personalized medicine; Medical physics; Bioinformatics; Pathology; Terminology; Genome; Biology","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":[0.0005837943,0.0001726229,0.0003632166,0.00002911631,0.0001087831,0.00005529039,0.0002336172,0.0004108562,0.00003523513],"category_scores_gemma":[0.000638968,0.0001649733,0.0002436178,0.0001218273,0.00008182973,0.000009736409,0.0001607939,0.0001694843,0.00001657733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002229939,"about_ca_system_score_gemma":0.001718889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000422575,"about_ca_topic_score_gemma":0.0006801855,"domain_scores_codex":[0.9980881,0.00006353934,0.00111528,0.0002690498,0.0001709417,0.0002930407],"domain_scores_gemma":[0.9979972,0.0002955284,0.0004657712,0.0005025392,0.0005660593,0.0001729275],"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":[0.001397304,0.0005807491,0.02007442,0.001074076,0.0004781369,0.000006354723,0.0005934155,0.002791491,0.0158215,0.004665901,0.2249195,0.7275971],"study_design_scores_gemma":[0.002134327,0.0004866675,0.00280155,0.0001046298,0.0001314602,0.000009708389,0.0008747531,0.005398564,0.01566004,0.00006953112,0.9720375,0.0002912855],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8649831,0.01153151,0.07298269,0.004298902,0.01427136,0.002552568,0.002671035,0.0001337804,0.02657503],"genre_scores_gemma":[0.9371547,0.0263664,0.01991609,0.006757363,0.005080816,0.001420286,0.001133812,0.00009087484,0.002079643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7471179,"threshold_uncertainty_score":0.6727417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08534025705951545,"score_gpt":0.4308628302471838,"score_spread":0.3455225731876683,"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."}}