{"id":"W2809234664","doi":"10.1093/neuonc/noy059.228","title":"EPEN-28. HETEROGENEITY WITHIN THE PFB EPENDYMOMA SUBGROUP","year":2018,"lang":"en","type":"article","venue":"Neuro-Oncology","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; Hospital for Sick Children","funders":"","keywords":"Proportional hazards model; Oncology; Internal medicine; Survival analysis; Medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002728231,0.0002285904,0.0004635933,0.0006768,0.000307021,0.0005094286,0.0002620986,0.0002654815,0.0016299],"category_scores_gemma":[0.0009634785,0.0001276519,0.0003071715,0.0004885596,0.0002353554,0.00034336,0.0004406052,0.0004053212,0.0003692259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004184563,"about_ca_system_score_gemma":0.0002785284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002369162,"about_ca_topic_score_gemma":0.003294138,"domain_scores_codex":[0.9997433,0.00002039508,0.00002294344,0.0001034262,0.00006356481,0.00004630987],"domain_scores_gemma":[0.9997433,0.00005336297,0.00007230227,0.00003673026,0.00003950003,0.00005478924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001554684,0.00009962284,0.756588,0.0001694145,0.0003594275,0.006910492,0.0005041637,0.002352669,0.1553956,0.0009943547,0.001311991,0.0737595],"study_design_scores_gemma":[0.00003108909,0.0001668206,0.9696714,0.00001725418,0.0001192079,0.0114123,0.0002403244,0.003328739,0.008068454,0.002513787,0.004411905,0.00001873296],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968808,0.0003904881,0.0009761528,0.00006728712,0.000002991687,0.00002083999,0.0005436516,0.00001688351,0.001100966],"genre_scores_gemma":[0.9978991,0.000106007,0.0004460627,0.00002516998,0.000005373523,0.00001531891,0.0009703435,0.00001228145,0.0005203396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002369162,"threshold_uncertainty_score":0.005452514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02166929663748141,"score_gpt":0.3301284806921344,"score_spread":0.308459184054653,"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."}}