{"id":"W4309017261","doi":"10.1093/neuonc/noac209.1133","title":"MODL-05. DISCOVERY OF DYNAMIC MINIMAL RESIDUAL DISEASE STATES IN ADULT GLIOBLASTOMA USING SINGLE CELL TECHNOLOGY","year":2022,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto; McMaster University","funders":"","keywords":"Glioblastoma; Multidrug tolerance; Minimal residual disease; Disease; Residual; Computational biology; Rapid cycling; Chemoradiotherapy; Biology; Cancer research; Cancer; Medicine; Genetics; Computer science; Pathology; Neuroscience; Bacteria; Algorithm","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":[0.0001167574,0.0002162178,0.0003261695,0.0002592875,0.0001074016,0.00001161738,0.0003611317,0.0001846181,0.00001639417],"category_scores_gemma":[0.00009092507,0.0002437371,0.0001033519,0.0003056293,0.0002527478,0.000009908045,0.0003535346,0.0003190834,0.000001237302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001595288,"about_ca_system_score_gemma":0.0003668101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007036206,"about_ca_topic_score_gemma":0.0002491094,"domain_scores_codex":[0.9981991,0.0002324453,0.0004362519,0.0005489265,0.0001690334,0.0004142421],"domain_scores_gemma":[0.9992352,0.00005838519,0.0001914774,0.0003667369,0.00006777179,0.00008043124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001848733,0.0009462601,0.003721933,0.00004102177,0.00001531068,0.0001921985,0.0001080149,0.003883916,0.9877645,0.00003411132,0.0001753074,0.001268724],"study_design_scores_gemma":[0.003833377,0.008556376,0.0007427999,0.00001736437,0.00008393422,0.0001323067,0.00121251,0.008771241,0.9657156,0.0003622445,0.01003409,0.0005381717],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977518,0.0003617297,0.0003247258,0.0005012222,0.0004522496,0.0002490237,0.0002027102,0.00002207101,0.0001344888],"genre_scores_gemma":[0.9985175,0.00008329035,0.0006220039,0.0004702391,0.00005958503,0.00003955754,0.0001033457,0.00004753811,0.00005695952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02204888,"threshold_uncertainty_score":0.9939311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0097194999590045,"score_gpt":0.2409012907235929,"score_spread":0.2311817907645884,"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."}}