{"id":"W3112969951","doi":"10.1016/j.jval.2020.08.1721","title":"PPM4 Health and Budget IMPACT of Liquid-Based Comprehensive Genomic Profile Testing (CGP) in Advance NON-SMALL CELL LUNG Cancer (ANSCLC) Patients with Insufficient Tissue, Exhausted Tissue Samples and or Insufficient DNA in Tissue Samples","year":2020,"lang":"en","type":"article","venue":"Value in Health","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"BC Cancer Agency; University Health Network; Princess Margaret Cancer Centre; University of Ottawa; Roche (Canada)","funders":"","keywords":"Medicine; Population; Biopsy; Liquid biopsy; Biomarker; Lung cancer; Health care; Cancer; Oncology; Intensive care medicine; Internal medicine; Pathology; Environmental health; Biology","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":[0.002160805,0.0002641061,0.0002488422,0.0007705197,0.000359443,0.001316353,0.0006583498,0.0005179039,0.01369617],"category_scores_gemma":[0.009276384,0.0001834708,0.0009196054,0.001135387,0.0004018999,0.0006475457,0.001847684,0.0006054917,0.0007741975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005164927,"about_ca_system_score_gemma":0.005612288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04786539,"about_ca_topic_score_gemma":0.03726379,"domain_scores_codex":[0.9976051,0.001184069,0.0001220642,0.0001739975,0.0003960318,0.0005187962],"domain_scores_gemma":[0.9951799,0.001391232,0.001315338,0.000145729,0.000852056,0.00111588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006003043,0.0003638896,0.8148729,0.0002997716,0.0004863663,0.0004555293,0.0001594861,0.01515857,0.001499254,0.003370954,0.01851353,0.1388167],"study_design_scores_gemma":[0.0003324679,0.001784231,0.9535916,0.0002814823,0.0004848254,0.0005256946,0.001016071,0.01523097,0.00169732,0.002664511,0.02234413,0.00004666793],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9252717,0.002320557,0.001863425,0.01873989,0.0002202258,0.0001232146,0.02483661,0.0001712535,0.026453],"genre_scores_gemma":[0.9923523,0.0003009664,0.0007206291,0.0006008591,0.00006091089,0.0000615111,0.003847539,0.00002217453,0.002033028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04786539,"threshold_uncertainty_score":0.09517354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03154745500702,"score_gpt":0.2990558695636786,"score_spread":0.2675084145566586,"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."}}