{"id":"W3037379129","doi":"10.1080/13696998.2020.1789152","title":"Costs of in-house genomic profiling and implications for economic evaluation: a case example of non-small cell lung cancer (NSCLC)","year":2020,"lang":"en","type":"article","venue":"Journal of Medical Economics","topic":"Lung Cancer Treatments and Mutations","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Spinal Cord Injury BC; Roche (Canada); William Osler Health System; Vancouver Coastal Health","funders":"","keywords":"Medicine; Profiling (computer programming); Activity-based costing; Lung cancer; Operations management; Oncology; Business; Accounting; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005228666,0.00008254098,0.0003969937,0.00008581056,0.00002374001,0.000006697094,0.00007984322,0.00007719278,0.00006935077],"category_scores_gemma":[0.00008046981,0.0000736928,0.00009102468,0.00003343518,0.0000474292,0.00006412435,0.00002448339,0.0001194689,4.676089e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004250572,"about_ca_system_score_gemma":0.002187067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000320116,"about_ca_topic_score_gemma":0.0002750681,"domain_scores_codex":[0.9989511,0.0000182871,0.000723819,0.0001327021,0.00006888666,0.0001052489],"domain_scores_gemma":[0.9988499,0.0001823855,0.0005087298,0.0000982837,0.0001171046,0.0002435625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002201021,0.001444174,0.740292,0.003194611,0.002708615,0.000190938,0.01399026,0.02457662,0.008645581,0.003867787,0.003432231,0.1954561],"study_design_scores_gemma":[0.09027176,0.00418758,0.15955,0.001771353,0.007623654,0.003153708,0.005475738,0.7084286,0.0135958,0.0009713797,0.004141641,0.0008288433],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912022,0.001674766,0.0009577889,0.005179161,0.0001173761,0.0006654572,0.00009659391,0.000002618769,0.0001040735],"genre_scores_gemma":[0.9948289,0.001355349,0.00317737,0.0003297821,0.0002312802,0.00004578819,0.000007451057,0.00002034717,0.000003694172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6838519,"threshold_uncertainty_score":0.3879763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04434937502367767,"score_gpt":0.3662375444127789,"score_spread":0.3218881693891013,"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."}}