{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007904491,0.0002174159,0.0005425675,0.0005628866,0.0002944713,0.0008393259,0.0003851174,0.0003913655,0.001501648],"category_scores_gemma":[0.0005980426,0.0002002879,0.0002594752,0.0004390162,0.0002726592,0.0002741646,0.0003912467,0.0005354331,0.0007620317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007709074,"about_ca_system_score_gemma":0.0006319685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001791094,"about_ca_topic_score_gemma":0.004152594,"domain_scores_codex":[0.9996623,0.00002383439,0.00002417635,0.0001096715,0.0001292659,0.00005074043],"domain_scores_gemma":[0.9996004,0.0001061225,0.00008712434,0.00005908585,0.00008258779,0.00006474629],"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":[0.0003469382,0.0000758689,0.01225617,0.0002289066,0.00003354899,0.0001130092,0.000116873,0.001177328,0.9576417,0.0008208632,0.002562665,0.02462605],"study_design_scores_gemma":[0.00007039478,0.0007333235,0.06795296,0.00004409935,0.00008716537,0.0005656517,0.0001605775,0.02636527,0.8725504,0.001174254,0.03025444,0.00004148696],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9353104,0.00190949,0.02849722,0.0004628874,0.00008616432,0.0002053104,0.02807292,0.001968757,0.003486882],"genre_scores_gemma":[0.9160636,0.0008898835,0.04504713,0.0004819024,0.00002813627,0.0004514489,0.03223395,0.0003674521,0.004436384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001791094,"threshold_uncertainty_score":0.005593359,"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."}}