{"id":"W2900040219","doi":"10.1016/j.jval.2018.07.019","title":"Cross-Country Comparison Of Cancer-Specific Multi-Attribute Utility Instruments (Mauis): Relative Weighting And Ranking Of Health-Related Quality Of Life (Hrql) Domains In Country-Specific Utility Algorithms","year":2018,"lang":"en","type":"article","venue":"Value in Health","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Centre for Applied Research in Cancer Control","funders":"","keywords":"Life expectancy; Quality of life (healthcare); Demography; Medicine; Representativeness heuristic; Ranking (information retrieval); Population; Valuation (finance); Statistics; Actuarial science; Gerontology; Econometrics; Mathematics; Computer science; Machine learning; Economics; Accounting; Environmental health","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":[0.03598393,0.0008154763,0.001328527,0.003717232,0.0003735924,0.002224308,0.001255582,0.00101774,0.00221629],"category_scores_gemma":[0.07019129,0.0003878828,0.003573262,0.004109293,0.0006374606,0.001752257,0.002895865,0.001513905,0.0003885277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009795374,"about_ca_system_score_gemma":0.0007232671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003512982,"about_ca_topic_score_gemma":0.002683343,"domain_scores_codex":[0.9849764,0.01248825,0.0006472167,0.0007306467,0.0007535553,0.000403928],"domain_scores_gemma":[0.9657119,0.02545081,0.002208241,0.003621924,0.002475538,0.0005314857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01423976,0.001359028,0.5868865,0.001324364,0.0167583,0.0001477702,0.001080925,0.1781274,0.001629384,0.02111962,0.007765293,0.1695618],"study_design_scores_gemma":[0.001749169,0.005292444,0.6268822,0.0007155457,0.006943566,0.0007119348,0.002146635,0.3228311,0.005061988,0.01822831,0.009111083,0.0003260757],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9357801,0.001882174,0.05360566,0.0002537559,0.00008916901,0.0003515075,0.005278667,0.0001236248,0.002635482],"genre_scores_gemma":[0.9695117,0.0003444318,0.02222013,0.00005411759,0.00001188311,0.0002632597,0.007281743,0.00006277954,0.0002499477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03598393,"threshold_uncertainty_score":0.1903035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4450046664542811,"score_gpt":0.4685143439618717,"score_spread":0.0235096775075907,"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."}}