{"id":"W4404237749","doi":"10.1093/neuonc/noae165.0098","title":"BIOM-25. MOLECULAR PROFILING PREDICTS EARLY AND LATE PROGRESSION IN GLIOBLASTOMA","year":2024,"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; St. Michael's Hospital; University of Toronto; SickKids Foundation; Hospital for Sick Children; Ontario Institute for Cancer Research","funders":"","keywords":"Glioblastoma; Profiling (computer programming); Cancer research; Computational biology; Oncology; Medicine; Biology; Computer science; Programming language","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":[0.0002945828,0.0002586749,0.0003349935,0.000965496,0.0002034927,0.0005164197,0.0001535119,0.0002765133,0.00199693],"category_scores_gemma":[0.0004996081,0.0001251195,0.0002277997,0.0004655793,0.0001718022,0.0001816753,0.0002313895,0.0002662399,0.0004916009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00037469,"about_ca_system_score_gemma":0.0001748982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00167038,"about_ca_topic_score_gemma":0.002071784,"domain_scores_codex":[0.9999065,0.00001451178,0.00001113691,0.00002212736,0.00002190449,0.00002380945],"domain_scores_gemma":[0.9997582,0.00003329694,0.00009319266,0.00001332552,0.00004370177,0.00005825472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00248997,0.0001361868,0.8953679,0.0001158547,0.0001004616,0.0003009838,0.00007309479,0.0006734144,0.07677589,0.00009885717,0.001129284,0.02273804],"study_design_scores_gemma":[0.00001552083,0.0003968924,0.9858574,0.0000101394,0.00006317951,0.0004354616,0.00008824837,0.001491874,0.01055512,0.0001286818,0.0009473647,0.00001005686],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969907,0.0007757578,0.0003433372,0.00005519795,0.000008982451,0.00001681106,0.00100804,0.00003113017,0.0007700509],"genre_scores_gemma":[0.9972082,0.0002065833,0.0005586584,0.00002860364,0.000005952997,0.00001734275,0.001239042,0.000006817325,0.0007287902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00199693,"threshold_uncertainty_score":0.006680429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01304013139363711,"score_gpt":0.3087337745049578,"score_spread":0.2956936431113206,"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."}}