{"id":"W4224238459","doi":"10.1126/sciadv.abi8618","title":"Monitoring and adapting cancer treatment using circulating tumor DNA kinetics: Current research, opportunities, and challenges","year":2022,"lang":"en","type":"review","venue":"Science Advances","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":185,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"","keywords":"Circulating tumor DNA; Cancer; Adaptation (eye); Precision medicine; Medicine; Biomarker; Cancer treatment; Computational biology; Clinical Practice; Kinetics; Oncology; Bioinformatics; Cancer research; Biology; Internal medicine; Pathology; Genetics; Neuroscience","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":[0.001631464,0.0009042783,0.001836552,0.001958277,0.0003114147,0.00180298,0.001147814,0.001729046,0.003035866],"category_scores_gemma":[0.002138236,0.0003781845,0.0008069671,0.001804408,0.0007390188,0.002069284,0.0009077257,0.002150163,0.001991316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008489685,"about_ca_system_score_gemma":0.001851033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001305989,"about_ca_topic_score_gemma":0.001930736,"domain_scores_codex":[0.9995165,0.0001065738,0.00005757139,0.0001015642,0.0001730252,0.00004484798],"domain_scores_gemma":[0.9986426,0.0008538596,0.0001123783,0.00003745949,0.0002947535,0.00005891738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007202925,0.00007805455,0.000307157,0.0169542,0.00008739919,0.0001238418,0.00008519866,0.0005679724,0.001784334,0.005932476,0.01426042,0.959747],"study_design_scores_gemma":[0.0000161198,0.0001691156,0.000812767,0.005739067,0.0001681223,0.000964094,0.0001531755,0.0003306867,0.001484317,0.004937666,0.985184,0.00004089445],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001313304,0.9981711,0.0003129405,0.000578865,0.0001510701,0.000005080207,0.00002048964,0.00001071887,0.0006183895],"genre_scores_gemma":[0.0009836562,0.9978275,0.0003741515,0.0002886948,0.0001455754,0.00001037734,0.00003177571,0.000003109549,0.0003352339],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003035866,"threshold_uncertainty_score":0.01015604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.42406088960205,"score_gpt":0.4609433625287622,"score_spread":0.03688247292671215,"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."}}