{"id":"W4384108628","doi":"10.1093/noajnl/vdad071.002","title":"MULTIPLATFORM MOLECULAR ANALYSIS OF VESTIBULAR SCHWANNOMA REVEALS TWO ROBUST SUBGROUPS WITH DISTINCT MICROENVIRONMENT","year":2023,"lang":"en","type":"article","venue":"Neuro-Oncology Advances","topic":"Meningioma and schwannoma management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computational biology; Biology; Drug repositioning; Schwannoma; Consensus clustering; Bioinformatics; Cluster analysis; Cancer research; Medicine; Computer science; Drug; Pathology; Artificial intelligence; Pharmacology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003594184,0.0002893965,0.0009104009,0.0006601581,0.0001167919,0.0000118837,0.0002107853,0.00008417532,0.0001096962],"category_scores_gemma":[0.0001380601,0.0002348515,0.0001624544,0.001651152,0.0003145559,0.0001482251,0.0001499271,0.000229452,0.00004760198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001039164,"about_ca_system_score_gemma":0.00004634659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001459466,"about_ca_topic_score_gemma":0.00002598506,"domain_scores_codex":[0.9977977,0.0001006688,0.0005472816,0.000630146,0.0004364456,0.0004878106],"domain_scores_gemma":[0.9985377,0.0002754347,0.0003279927,0.0006085184,0.00006378066,0.0001866244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001683745,0.0006327614,0.3926687,0.0003553149,0.003198151,0.02055747,0.0003785916,0.07227184,0.4993991,0.001133678,0.000566984,0.007153628],"study_design_scores_gemma":[0.01149669,0.01023063,0.8420771,0.0002571742,0.01404762,0.0009134849,0.001070893,0.02261983,0.04350955,0.0005387638,0.05200128,0.001236968],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936591,0.0006198178,0.002379037,0.000661299,0.0001239191,0.0006108443,0.00002439563,0.0001307919,0.001790824],"genre_scores_gemma":[0.9930441,0.00006807449,0.006122663,0.0002135815,0.00004344864,0.00008888295,0.0001668741,0.00003724883,0.0002151716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4558896,"threshold_uncertainty_score":0.9576967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01949899788783256,"score_gpt":0.286669645388796,"score_spread":0.2671706475009635,"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."}}