{"id":"W4414011763","doi":"10.36401/jipo-25-11","title":"Circulating Tumor DNA as a Prognostic Biomarker for Selecting Participants to Early Phase Clinical Trials","year":2025,"lang":"en","type":"article","venue":"Journal of Immunotherapy and Precision Oncology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Loxo Oncology; Chugai Pharmaceutical; Foundation Medicine; Sierra Oncology; Servier; Ministry of Minority Affairs; European Society for Medical Oncology; Astellas Pharma; Eisai; Cancer Research UK; Seagen; Actuate Therapeutics; Pfizer; Incyte; NuCana; Moderna; Tarveda Therapeutics; Taiho Pharmaceutical; Christie Charity; MacroGenics; Sarcoma UK; Sanofi; GlaxoSmithKline; Amgen; Carrick Therapeutics; AstraZeneca; Ignyta; Eli Lilly and Company; Bristol-Myers Squibb","keywords":"Biomarker; Oncology; Clinical trial; Medicine; Circulating tumor DNA; Internal medicine; Computational biology; Cancer; Biology; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04043097,0.0004695647,0.0007790702,0.001535813,0.0005758477,0.002223221,0.0008504774,0.001191601,0.003911166],"category_scores_gemma":[0.06147365,0.0002515626,0.0006263849,0.001306054,0.0005778202,0.001503593,0.0007413187,0.0007761857,0.0008848158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004829798,"about_ca_system_score_gemma":0.001132979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001715799,"about_ca_topic_score_gemma":0.000348831,"domain_scores_codex":[0.9824723,0.01197404,0.00190021,0.001174349,0.001859788,0.0006193955],"domain_scores_gemma":[0.9386275,0.03690701,0.01692148,0.001644725,0.003671335,0.002227911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0134057,0.0003824938,0.8314859,0.0005720085,0.0003036938,0.0001910517,0.0003626855,0.001207802,0.005683927,0.0009055057,0.004215163,0.1412841],"study_design_scores_gemma":[0.002716129,0.01550041,0.9196006,0.0008323779,0.000831843,0.002208561,0.0004972548,0.01578679,0.01494386,0.006676746,0.02026075,0.0001446019],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9497011,0.007976843,0.0268476,0.003276553,0.000397621,0.002041679,0.002545648,0.0004011412,0.006811942],"genre_scores_gemma":[0.9785679,0.0004620331,0.01794946,0.000543282,0.000202398,0.001159057,0.0007051777,0.00002818839,0.0003824746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04043097,"threshold_uncertainty_score":0.2138219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1178469495001141,"score_gpt":0.4979265712615337,"score_spread":0.3800796217614197,"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."}}