{"id":"W4416141195","doi":"10.1093/neuonc/noaf201.0189","title":"BIOM-101. STRATIFICATION OF GLIOBLASTOMA PROGRESSORS USING MULTI-OMIC PROFILING AND GRAPH NEURAL NETWORKS","year":2025,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Glioma Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Hospital; Orthopaedic Innovation Centre; University of Toronto","funders":"","keywords":"Interpretability; Glioblastoma; Concordance; CDKN2A; Gene expression profiling; Proportional hazards model; Gene; Cohort; PTEN","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":[0.0007598339,0.000676515,0.0004326144,0.001381807,0.0002269551,0.0005495659,0.0004716732,0.0005558862,0.00129997],"category_scores_gemma":[0.001933098,0.000218328,0.0009742336,0.0005818246,0.0001951896,0.0002917731,0.0004530097,0.0004586345,0.0003699374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001016452,"about_ca_system_score_gemma":0.0007199068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01272435,"about_ca_topic_score_gemma":0.01146125,"domain_scores_codex":[0.9997855,0.00008794269,0.00001150173,0.00007014452,0.00002359641,0.00002132933],"domain_scores_gemma":[0.99958,0.0002171689,0.00007986608,0.00003110494,0.00006159442,0.00003035393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001067963,0.0003554221,0.08899012,0.0002266956,0.0007186782,0.0002085022,0.00007080103,0.7687683,0.005821683,0.002206329,0.005013753,0.1265517],"study_design_scores_gemma":[0.000009672259,0.00004166794,0.004496487,0.000007395524,0.00002594849,0.00001853891,0.000006984535,0.993279,0.0003482976,0.001483327,0.0002774849,0.000005138524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7762465,0.001360558,0.2020293,0.001908603,0.0001105093,0.0002668544,0.0118874,0.002619787,0.003570539],"genre_scores_gemma":[0.960729,0.0001949756,0.02951562,0.0001455331,0.00003309095,0.0001445217,0.007660457,0.00005554537,0.001521311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01272435,"threshold_uncertainty_score":0.02530056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02917649020331111,"score_gpt":0.3341762339109622,"score_spread":0.3049997437076511,"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."}}