{"id":"W4387810683","doi":"10.1016/j.annonc.2023.09.2394","title":"1361P Alectinib for treatment-naïve advanced ALK+ NSCLC selected via blood-based NGS: Updated analyses of outcomes, circulating tumour (ct)DNA and biomarker subgroups from BFAST Cohort A","year":2023,"lang":"en","type":"article","venue":"Annals of Oncology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre","funders":"F. Hoffmann-La Roche","keywords":"Medicine; Alectinib; Internal medicine; Cohort; Oncology; Population; Clinical endpoint; Biomarker; Crizotinib; Clinical trial; Lung 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":[0.0008431303,0.0004209336,0.0005996027,0.0004632092,0.000274734,0.001068695,0.0004469442,0.0003138097,0.001552228],"category_scores_gemma":[0.001226566,0.000242904,0.0008947001,0.0008284553,0.0001737178,0.0005885176,0.0005512347,0.0007113002,0.0003928995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005623313,"about_ca_system_score_gemma":0.0005881733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006711917,"about_ca_topic_score_gemma":0.01501935,"domain_scores_codex":[0.9996738,0.00005202486,0.00002549203,0.0001150445,0.00007385781,0.00005976507],"domain_scores_gemma":[0.9994594,0.00009095911,0.0001593884,0.00009782174,0.00009330175,0.00009907691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007813388,0.0001003034,0.9153064,0.0001584839,0.002121226,0.000228701,0.0001006667,0.001055881,0.007349336,0.0002153914,0.008185558,0.05736469],"study_design_scores_gemma":[0.0002819391,0.0003686576,0.9890787,0.00004136294,0.001339041,0.0005151615,0.00009305712,0.001135636,0.0009755893,0.0003755571,0.005775644,0.00001961363],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9801697,0.001973655,0.0006549,0.0003226966,0.00006502281,0.0000352103,0.01491185,0.00005925817,0.001807804],"genre_scores_gemma":[0.9777539,0.0006899375,0.0006729982,0.0002242215,0.00006790804,0.00004108251,0.01927426,0.00003169208,0.001243974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006711917,"threshold_uncertainty_score":0.01334572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06078886281150758,"score_gpt":0.3755104978870426,"score_spread":0.314721635075535,"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."}}