{"id":"W4404580899","doi":"10.1016/j.jlb.2024.100178","title":"Expanding clinical impact of liquid biopsy beyond genomics: exploration of novel epigenomic applications","year":2024,"lang":"en","type":"article","venue":"The Journal of Liquid Biopsy","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network","funders":"","keywords":"Epigenomics; Genomics; Liquid biopsy; Computer science; Computational biology; Data science; Medicine; Biology; DNA methylation; Internal medicine; Genome; Genetics; Gene; Cancer","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":[0.004373888,0.0006870823,0.0007058013,0.001829472,0.0004594158,0.002049388,0.0006838132,0.000810353,0.004140652],"category_scores_gemma":[0.005161312,0.0003380956,0.0003594658,0.0009495401,0.0006527866,0.0006849595,0.00190914,0.0006642121,0.0008166536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006891168,"about_ca_system_score_gemma":0.000960513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001615628,"about_ca_topic_score_gemma":0.003008541,"domain_scores_codex":[0.9975756,0.001145348,0.0001076373,0.0005176624,0.0004594745,0.0001942784],"domain_scores_gemma":[0.9972287,0.001479473,0.0003253981,0.0002437005,0.0004194991,0.0003032123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003103099,0.0002407669,0.6180296,0.0008204761,0.0002982334,0.003216754,0.0008491145,0.001741551,0.142783,0.001430637,0.004132076,0.2233548],"study_design_scores_gemma":[0.0002485068,0.002461766,0.8150592,0.0007946743,0.0007819594,0.01900958,0.001851969,0.01857596,0.09520046,0.004473927,0.04145182,0.00009015379],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.9263515,0.01615871,0.04156346,0.002383602,0.0001691176,0.0003576167,0.002847644,0.0007789135,0.00938956],"genre_scores_gemma":[0.9713508,0.001632987,0.02360867,0.0008259638,0.00013729,0.0001205791,0.001212076,0.0001077875,0.001003649],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004373888,"threshold_uncertainty_score":0.02313161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03791260406424355,"score_gpt":0.3532069467123957,"score_spread":0.3152943426481521,"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."}}