{"id":"W2564219340","doi":"10.1158/1538-7445.am2015-5297","title":"Abstract 5297: Chromosomal instability as a prognostic marker in cervical cancer","year":2015,"lang":"en","type":"article","venue":"Cancer Research","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Cervical cancer; Medicine; Hazard ratio; Cancer; Oncology; Internal medicine; Cohort; Chromosome instability; Proportional hazards model; Gastroenterology; Gene; Confidence interval; Biology; Genetics; Chromosome","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":[0.000338272,0.0001394312,0.0002566303,0.001524315,0.0002924775,0.0005849266,0.0002482244,0.0002734134,0.004887945],"category_scores_gemma":[0.001959761,0.00008806889,0.000145544,0.001696898,0.0001699575,0.0001999814,0.0003812935,0.0002565609,0.0007211174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00040241,"about_ca_system_score_gemma":0.000363248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003049167,"about_ca_topic_score_gemma":0.004708234,"domain_scores_codex":[0.9998131,0.00003008133,0.0000181471,0.00003106734,0.0000811503,0.00002643209],"domain_scores_gemma":[0.9993462,0.0001573904,0.0002101136,0.00003257541,0.0001556316,0.00009807134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008880493,0.0000191537,0.9561304,0.00008135624,0.00005568204,0.0004115078,0.0001017951,0.00018567,0.005956114,0.00009181844,0.003848647,0.03222981],"study_design_scores_gemma":[0.00001745394,0.0001405936,0.9926958,0.00002820459,0.0000583844,0.001430442,0.0000867491,0.0005683524,0.001809018,0.0001272288,0.003027887,0.00000982718],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896651,0.002490304,0.0003883199,0.0006961346,0.00006812845,0.00003152035,0.002732569,0.0000490129,0.003879],"genre_scores_gemma":[0.9962107,0.0005582357,0.0003839816,0.0000766198,0.00005691685,0.00001454148,0.001190837,0.000009150581,0.001499125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004887945,"threshold_uncertainty_score":0.01635176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08298458269265552,"score_gpt":0.4480421633303485,"score_spread":0.3650575806376929,"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."}}