{"id":"W3200402883","doi":"10.1093/neuonc/noab227","title":"Impact of the methylation classifier and ancillary methods on CNS tumor diagnostics","year":2021,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Glioma Diagnosis and Treatment","field":"Medicine","cited_by":107,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Cancer Institute; National Institutes of Health; Center for Cancer Research","keywords":"Classifier (UML); Confidence interval; Medicine; Methylation; Oncology; DNA methylation; Brain tumor; Artificial intelligence; Internal medicine; Pathology; Computer science; Biology","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":[0.0001806951,0.000119255,0.0003462949,0.00005459465,0.00005040969,0.000005845631,0.00004017899,0.00009343735,0.00007807944],"category_scores_gemma":[0.001754558,0.00007184059,0.0001495528,0.0002063616,0.0000839551,0.00001926512,0.00006583596,0.0001818349,0.000004494973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001510698,"about_ca_system_score_gemma":0.0003218421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001649171,"about_ca_topic_score_gemma":0.00001481863,"domain_scores_codex":[0.9988429,0.000436612,0.0002080417,0.0002227421,0.0001315046,0.0001581924],"domain_scores_gemma":[0.9972341,0.002127468,0.000119128,0.0003045669,0.0001189665,0.00009577816],"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":[0.0001203475,0.001063674,0.3045522,0.00002606433,0.0001768552,0.0006171642,0.0002036603,0.00003722714,0.6048072,0.0004820911,0.00407393,0.08383957],"study_design_scores_gemma":[0.001808437,0.00196329,0.7426012,0.00002839964,0.0002924696,0.0003051715,0.00004732271,0.0001660795,0.2297587,0.0002229126,0.02274225,0.00006376013],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921505,0.0008532489,0.00003514365,0.003577857,0.00035787,0.0002673661,0.00001635684,0.00001294989,0.002728692],"genre_scores_gemma":[0.9960749,0.000466359,0.001676609,0.001631534,0.00008687771,0.00002731454,0.000008278853,0.000016018,0.00001214768],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.438049,"threshold_uncertainty_score":0.2929575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04601508791301511,"score_gpt":0.3890986404856309,"score_spread":0.3430835525726158,"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."}}