{"id":"W3008822475","doi":"10.2217/lmt-2019-0017","title":"Optimizing Molecular Residual Disease Detection using Liquid Biopsy Postoperatively in Early Stage Lung Cancer","year":2020,"lang":"en","type":"editorial","venue":"Lung Cancer Management","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; Vancouver General Hospital; University of British Columbia","funders":"","keywords":"Stage (stratigraphy); Medicine; Disease; Lung cancer; Residual; Liquid biopsy; Lung; Biopsy; Cancer; Radiology; Oncology; Pathology; Internal medicine; Biology; Computer science","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":[0.006779101,0.002537575,0.002553863,0.001696655,0.001198679,0.004228581,0.002426455,0.01068912,0.004308667],"category_scores_gemma":[0.01611148,0.0009880475,0.001581666,0.000925866,0.001348381,0.003174372,0.001000656,0.0211003,0.005270771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00270524,"about_ca_system_score_gemma":0.002197218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002170188,"about_ca_topic_score_gemma":0.006025629,"domain_scores_codex":[0.9975266,0.0005712486,0.0003726828,0.000290399,0.001096344,0.0001426987],"domain_scores_gemma":[0.9862059,0.006551415,0.0005392599,0.0002353814,0.004992881,0.001475148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001466352,0.00002419064,0.00007539348,0.0003052099,0.00002997375,0.0001131189,0.000008252317,0.00005358551,0.0001405889,0.0004024636,0.9787098,0.01999074],"study_design_scores_gemma":[0.000281997,0.0001547983,0.001257706,0.0009045202,0.0001937072,0.0005230156,0.00004087189,0.0006485333,0.0003834581,0.001998951,0.9935648,0.00004766075],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0001135498,0.01784377,0.0004371208,0.07412593,0.9050629,0.00004581144,0.0001271222,0.00009373006,0.002149974],"genre_scores_gemma":[0.0007218946,0.01145801,0.0003535046,0.04347593,0.9367911,0.00004735767,0.0000716686,0.00004081996,0.007039758],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.01068912,"threshold_uncertainty_score":0.03585178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007219570324032935,"score_gpt":0.285130474595809,"score_spread":0.2779109042717761,"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."}}