{"id":"W4404237224","doi":"10.1093/neuonc/noae165.0307","title":"RADT-23. MOLECULAR PROFILING OF GLIOMAS: INSIGHTS INTO RADIONECROSIS AND PSEUDOPROGRESSION THROUGH NEXT-GENERATION SEQUENCING","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":"Queen's University","funders":"","keywords":"Profiling (computer programming); Medicine; Computer science","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":[0.0009528779,0.0003187791,0.0004531481,0.001863418,0.0002316168,0.001002259,0.0003609918,0.0004453243,0.001544818],"category_scores_gemma":[0.001397044,0.0001649231,0.0005015831,0.001433256,0.000230856,0.0002195017,0.0002736663,0.000326348,0.0008809705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005867796,"about_ca_system_score_gemma":0.0005434282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002720446,"about_ca_topic_score_gemma":0.003749613,"domain_scores_codex":[0.9994345,0.0001182197,0.00007462124,0.0001597929,0.0001599338,0.00005298695],"domain_scores_gemma":[0.9992112,0.0001872528,0.0003118774,0.00005589554,0.0001711978,0.00006265361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001088344,0.000147202,0.6193197,0.00139268,0.0004891203,0.004081001,0.0004230114,0.002794437,0.1643811,0.0007866995,0.004837458,0.2002592],"study_design_scores_gemma":[0.00007697327,0.0007358306,0.7703762,0.0003768158,0.0007992581,0.0161234,0.0005277502,0.01511282,0.1433398,0.001315384,0.05111117,0.0001045638],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9312109,0.03080936,0.01075857,0.0008873181,0.0001352972,0.0002452681,0.01948463,0.0006394566,0.00582918],"genre_scores_gemma":[0.9590478,0.006784115,0.01858424,0.0004652494,0.00005914847,0.0001747463,0.01131663,0.00009806005,0.00347004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002720446,"threshold_uncertainty_score":0.0054093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05263591488240864,"score_gpt":0.3246426146994567,"score_spread":0.2720066998170481,"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."}}