{"id":"W2939075527","doi":"10.1177/2381468319842532","title":"The EORTC QLU-C10D: The Canadian Valuation Study and Algorithm to Derive Cancer-Specific Utilities From the EORTC QLQ-C30","year":2019,"lang":"en","type":"article","venue":"MDM Policy & Practice","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Canadian Centre for Applied Research in Cancer Control; Simon Fraser University","funders":"Canadian Cancer Society Research Institute","keywords":"Valuation (finance); Algorithm; Mathematics; Medicine; Statistics; Economics; Finance","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.007253827,0.00109133,0.001051029,0.003189136,0.001189124,0.001736932,0.00201518,0.0005309148,0.01131451],"category_scores_gemma":[0.02334679,0.0004781461,0.001803528,0.004891156,0.0006944455,0.0006619085,0.002353091,0.001482934,0.001266786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01946402,"about_ca_system_score_gemma":0.03145234,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7210084,"about_ca_topic_score_gemma":0.7600822,"domain_scores_codex":[0.9963126,0.001213305,0.0002435226,0.0002474288,0.001684954,0.0002982711],"domain_scores_gemma":[0.9958003,0.001009813,0.0003242642,0.0001901746,0.002446987,0.0002284077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001392657,0.0003033521,0.08345746,0.001960892,0.0006629832,0.0002291611,0.001123567,0.02398067,0.001082955,0.05750018,0.240285,0.5880211],"study_design_scores_gemma":[0.001887345,0.0004712483,0.4086821,0.002020948,0.0005797544,0.0009483327,0.001219444,0.1606614,0.002562557,0.05398206,0.3663863,0.0005983888],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1298569,0.009471728,0.4768268,0.00727336,0.0004168259,0.02881849,0.1782093,0.002657146,0.1664696],"genre_scores_gemma":[0.3002581,0.004235005,0.5888062,0.0009731696,0.00004686838,0.01793985,0.06705582,0.0007740267,0.01991091],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2789916,"threshold_uncertainty_score":0.5612693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3324208609108515,"score_gpt":0.4695284347940639,"score_spread":0.1371075738832123,"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."}}