{"id":"W3087777340","doi":"10.1016/j.annonc.2020.08.089","title":"1195P The value of detecting resistance through liquid biopsy","year":2020,"lang":"en","type":"article","venue":"Annals of Oncology","topic":"Lung Cancer Treatments and Mutations","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Regional Municipality of Niagara; Juravinski Cancer Centre; McGill University; University of Calgary; Jewish General Hospital; University Health Network; BC Cancer Agency; Princess Margaret Cancer Centre; Ottawa Hospital","funders":"","keywords":"Medicine; Liquid biopsy; Biopsy; T790M; Targeted therapy; Oncology; Lung cancer; Internal medicine; Cohort; Cancer; Clinical trial; Adenocarcinoma; Pathology; Bioinformatics; ROS1","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":[0.001350141,0.0005478225,0.0006737364,0.001269244,0.0006152672,0.001989641,0.0006320724,0.002681244,0.03077165],"category_scores_gemma":[0.008702872,0.000222172,0.0004498786,0.0007865634,0.0007027917,0.001179067,0.0005058424,0.002054235,0.008812263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009548773,"about_ca_system_score_gemma":0.0006359296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002951357,"about_ca_topic_score_gemma":0.002665906,"domain_scores_codex":[0.9986883,0.0004599458,0.00009729612,0.0002035149,0.0004282087,0.0001228061],"domain_scores_gemma":[0.9953201,0.002743237,0.0003981006,0.0002780545,0.0009643003,0.0002962583],"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":[0.003936614,0.0003712267,0.1278576,0.0005225427,0.0003185287,0.00648274,0.0001602827,0.001118954,0.03434584,0.007822433,0.1497654,0.667298],"study_design_scores_gemma":[0.001014458,0.00241769,0.2021129,0.001893454,0.0008060176,0.04585366,0.000941263,0.02581262,0.08224025,0.06199534,0.574695,0.0002174772],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.3355977,0.04723485,0.0257393,0.2329121,0.01296994,0.0002692876,0.01259752,0.003157342,0.329522],"genre_scores_gemma":[0.9110566,0.007047054,0.01409751,0.02625968,0.004153413,0.0001302744,0.002513508,0.0005045374,0.03423725],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03077165,"threshold_uncertainty_score":0.1029414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09487938942729415,"score_gpt":0.4398191624600701,"score_spread":0.344939773032776,"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."}}