{"id":"W4413856474","doi":"10.1093/noajnl/vdaf166.033","title":"34 RISK STRATIFICATION USING DEEP FEATURES IN IDH-MUTANT GLIOMAS","year":2025,"lang":"en","type":"article","venue":"Neuro-Oncology Advances","topic":"Glioma Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Risk stratification; Mutant; Stratification (seeds); Glioma; Biology; Internal medicine; Cancer research; Medicine; Genetics; Gene; Botany","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":[0.0005750089,0.0005705547,0.0004130676,0.001277326,0.0001293456,0.0006682713,0.0003862073,0.0004032166,0.0006897055],"category_scores_gemma":[0.001505346,0.0001200843,0.0004138762,0.0003595523,0.0001828875,0.000346679,0.0005465929,0.0004673334,0.0002360408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004651918,"about_ca_system_score_gemma":0.0004557369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004335905,"about_ca_topic_score_gemma":0.004468632,"domain_scores_codex":[0.9997843,0.00005768114,0.00001949705,0.00005252939,0.00004035181,0.00004553755],"domain_scores_gemma":[0.9995214,0.0001964378,0.00008968882,0.00004607069,0.00009779235,0.00004862384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001117533,0.0003640929,0.3272811,0.0001556894,0.0002869804,0.0008225994,0.0001313251,0.200509,0.02819886,0.001375353,0.006685381,0.4330721],"study_design_scores_gemma":[0.0000289162,0.0001327012,0.04014147,0.00003394985,0.00005620448,0.0002758186,0.00006590739,0.9451286,0.009407742,0.003819469,0.000885307,0.00002400303],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9415559,0.0005934222,0.0548132,0.0004478598,0.00003295477,0.00004242588,0.0009577034,0.0007830873,0.0007733324],"genre_scores_gemma":[0.9912527,0.00006173427,0.007469405,0.00003227876,0.00001253044,0.00001041792,0.0008094215,0.00001455214,0.0003368852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004335905,"threshold_uncertainty_score":0.008621335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01404621031242151,"score_gpt":0.3328721299870977,"score_spread":0.3188259196746762,"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."}}