{"id":"W4398781351","doi":"10.1017/cjn.2024.72","title":"GR.5 Establishing the utility of multi-platform liquid biopsy by integrating the CSF methylome and proteome in CNS malignancy","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Glioma Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Public Health","funders":"","keywords":"Liquid biopsy; DNA methylation; Lymphoma; Cerebrospinal fluid; Proteome; Computational biology; Shotgun; Malignancy; Medicine; Biopsy; Bioinformatics; Pathology; Oncology; Biology; Cancer; Internal medicine; Gene; Gene expression; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.003204472,0.0007705821,0.0007765086,0.002386721,0.0003866761,0.001905115,0.000518623,0.0008009948,0.002005079],"category_scores_gemma":[0.006321178,0.0002208545,0.0006821342,0.0007684182,0.0004456384,0.000766787,0.00110203,0.0006487184,0.0008441994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007918446,"about_ca_system_score_gemma":0.0008305704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003477588,"about_ca_topic_score_gemma":0.004804244,"domain_scores_codex":[0.9986211,0.0003809673,0.0001147601,0.0003159261,0.000416304,0.0001509661],"domain_scores_gemma":[0.9977406,0.0009186016,0.0004172102,0.0001915946,0.0005214571,0.0002105248],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00175966,0.0001868466,0.8549278,0.0002747762,0.0007212726,0.0002940253,0.000180265,0.0063763,0.04089469,0.0002794442,0.001269269,0.09283562],"study_design_scores_gemma":[0.0001098028,0.002195336,0.7429137,0.0002332961,0.001122374,0.002467335,0.0005801309,0.1626629,0.0799244,0.002338646,0.005348822,0.0001033337],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9729705,0.001756992,0.01967059,0.0003218677,0.00006366938,0.0001708884,0.002576774,0.0003547118,0.002113939],"genre_scores_gemma":[0.9822975,0.0002015611,0.01584092,0.00007331111,0.00002906414,0.00006156399,0.001124474,0.00003045535,0.000341162],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003477588,"threshold_uncertainty_score":0.01694703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04806316139851225,"score_gpt":0.2972892411650318,"score_spread":0.2492260797665196,"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."}}