{"id":"W3037925455","doi":"10.1016/j.clon.2020.05.022","title":"Emerging Precision Oncology Applications of Liquid Biopsy using Circulating Tumour DNA and Methylome Profiling","year":2020,"lang":"en","type":"article","venue":"Clinical Oncology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto; Ontario Institute for Cancer Research","funders":"Princess Margaret Cancer Foundation; Canadian Cancer Society Research Institute; Canadian Institutes of Health Research; Cancer Research Society; Bristol-Myers Squibb; Conquer Cancer Foundation","keywords":"Liquid biopsy; Medicine; DNA methylation; Precision oncology; Profiling (computer programming); Oncology; Biopsy; Circulating tumor DNA; Cell-free fetal DNA; DNA profiling; Precision medicine; Internal medicine; Computational biology; DNA; Cancer research; Pathology; Cancer; Gene; Genetics; Gene expression; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006882887,0.0001318849,0.0004679579,0.00003581715,0.00007563359,0.000007275625,0.0001728232,0.0003753383,0.00001110289],"category_scores_gemma":[0.001427145,0.0001352972,0.0001290329,0.0001382962,0.000216376,0.000003535673,0.0003378906,0.000210885,0.00000341429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000374782,"about_ca_system_score_gemma":0.000462696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001094373,"about_ca_topic_score_gemma":0.000007329437,"domain_scores_codex":[0.9981962,0.0001774279,0.0008539744,0.0004842956,0.00007520226,0.0002128784],"domain_scores_gemma":[0.9985408,0.0004822941,0.0004222681,0.0002068602,0.0001415602,0.0002062256],"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":[0.0003334677,0.0001503056,0.002853639,0.00004038428,0.00006416756,0.000009153967,0.00008667706,0.0002899955,0.939891,0.0002332079,0.00008038875,0.05596765],"study_design_scores_gemma":[0.006683638,0.0183883,0.005546528,0.000081405,0.0006096499,0.000225964,0.00145447,0.01589603,0.5676688,0.001224698,0.3810445,0.001176023],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9757128,0.00105681,0.02114666,0.0008626413,0.000239691,0.0003565617,0.00002676626,0.0000109158,0.0005871488],"genre_scores_gemma":[0.970215,0.0005784206,0.02717784,0.0009163555,0.001006832,0.00002906132,0.00004556886,0.00002385355,0.000007102105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3809641,"threshold_uncertainty_score":0.551726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07725865665633729,"score_gpt":0.4183758157014852,"score_spread":0.3411171590451479,"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."}}