{"id":"W3215696868","doi":"10.1093/neuonc/noab196.498","title":"PATH-46. DIAGNOSTIC IMPACT OF THE CNS TUMOR METHYLATION PROFILING IN A NEUROPATHOLOGY CONSULT PRACTICE","year":2021,"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":"University of Toronto","funders":"","keywords":"Neuropathology; Classifier (UML); Brain tumor; Medulloblastoma; Methylation; Medicine; DNA methylation; Profiling (computer programming); Oncology; Pathology; Internal medicine; Artificial intelligence; Computer science; Biology; Disease","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":[0.004543137,0.0003008905,0.0003374628,0.001138194,0.0005948237,0.001309556,0.0005171149,0.000488785,0.003059086],"category_scores_gemma":[0.0228254,0.0002101186,0.0003801929,0.0009814295,0.0005173087,0.0005694787,0.001110825,0.0004865442,0.0009744127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00124203,"about_ca_system_score_gemma":0.001729933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007614602,"about_ca_topic_score_gemma":0.01557483,"domain_scores_codex":[0.9957908,0.001915816,0.0002923352,0.0007769242,0.0009238292,0.0003003837],"domain_scores_gemma":[0.9886077,0.005582666,0.002440413,0.0006690233,0.001837809,0.0008624063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004877236,0.00009735193,0.9263839,0.0001043374,0.00009896868,0.0006373138,0.000298263,0.001552968,0.004382689,0.0001397423,0.001031791,0.064785],"study_design_scores_gemma":[0.00002427735,0.0008214305,0.9679959,0.00008130658,0.0001473819,0.002508398,0.0007678684,0.0182472,0.006967336,0.0005019389,0.001903274,0.00003366297],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916188,0.0005854973,0.003798862,0.0008117987,0.00002574526,0.00005258116,0.0007278589,0.0001432511,0.002235534],"genre_scores_gemma":[0.9958924,0.0001024553,0.00344364,0.00006288614,0.00001021587,0.00001056245,0.0002584772,0.00001249283,0.0002068417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007614602,"threshold_uncertainty_score":0.02402669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01584771785367732,"score_gpt":0.3542043586728391,"score_spread":0.3383566408191617,"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."}}