{"id":"W4388589017","doi":"10.1093/neuonc/noad179.1097","title":"TMIC-31. MULTI-PLATFORM GENOMIC LANDSCAPE OF INTRA-TUMORAL HYPOXIA IN GLIOBLASTOMA","year":2023,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Cancer, Hypoxia, and Metabolism","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University; University Health Network; University of Toronto; The Scarborough Hospital; Toronto Western Hospital; Princess Margaret Cancer Centre","funders":"","keywords":"Transcriptome; Biology; Laser capture microdissection; Epigenomics; Hypoxia (environmental); Chromatin; DNA methylation; Gene expression profiling; Cancer research; Gene expression; Computational biology; Gene; Genetics; Chemistry","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":[0.000124712,0.0001923668,0.0002798714,0.0004099356,0.0002280694,0.0002940073,0.0001126568,0.0001851869,0.001597151],"category_scores_gemma":[0.0001808566,0.0001168491,0.0001941689,0.0005351703,0.0001398419,0.00008530614,0.0001977897,0.0002262777,0.0003510498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002797652,"about_ca_system_score_gemma":0.0002856914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001781497,"about_ca_topic_score_gemma":0.002584722,"domain_scores_codex":[0.9998922,0.00000953843,0.000005200337,0.00002881711,0.00003663441,0.00002751521],"domain_scores_gemma":[0.9999055,0.00001149063,0.0000304635,0.000008870179,0.00002151614,0.00002204086],"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":[0.0005606081,0.0000210306,0.01128289,0.000116184,0.00002675845,0.0001405952,0.00004185619,0.0006165081,0.9779027,0.0000902977,0.0005497852,0.008650634],"study_design_scores_gemma":[0.00004951136,0.001116244,0.3910078,0.00003492824,0.0001864481,0.00196998,0.0002966743,0.009829047,0.5838452,0.0004993042,0.01113138,0.00003353137],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984872,0.001724859,0.00379562,0.0001409115,0.00002513883,0.00005071064,0.007444132,0.0002532666,0.001693293],"genre_scores_gemma":[0.987074,0.0005739621,0.002982919,0.00009090419,0.000007863212,0.00006744103,0.00779146,0.00003283586,0.00137843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001781497,"threshold_uncertainty_score":0.00534296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01707176169375921,"score_gpt":0.2731218528501231,"score_spread":0.2560500911563639,"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."}}