{"id":"W3011871823","doi":"10.1186/s41687-020-0175-5","title":"Japanese health utilities index mark 3 (HUI3): measurement properties in a community sample","year":2020,"lang":"en","type":"article","venue":"Journal of Patient-Reported Outcomes","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health","keywords":"Interpretability; Psychology; Sample (material); Statistics; Quality of life (healthcare); Index (typography); Gerontology; Clinical psychology; Econometrics; Medicine; Mathematics; Artificial intelligence; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01155226,0.0004042439,0.0004936067,0.001130682,0.0006620908,0.0006998459,0.0005729648,0.0003813397,0.002271608],"category_scores_gemma":[0.02307294,0.0002245234,0.001088674,0.001913458,0.000565054,0.0005236197,0.0008983407,0.0004725219,0.0004143206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006953159,"about_ca_system_score_gemma":0.001050315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007042236,"about_ca_topic_score_gemma":0.008089543,"domain_scores_codex":[0.9953167,0.002109479,0.0006538286,0.0004345374,0.001289915,0.0001954043],"domain_scores_gemma":[0.9917196,0.003020316,0.001591681,0.0009494018,0.002388627,0.0003303629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007301419,0.0002679658,0.9416558,0.0002973146,0.0004177378,0.0001222399,0.001405241,0.0008570867,0.0008386184,0.0003784393,0.002523746,0.05050582],"study_design_scores_gemma":[0.00006647268,0.0003741726,0.9932306,0.00004796942,0.0001959273,0.0003124273,0.000454317,0.002170422,0.0003861728,0.0004120172,0.002323113,0.00002636697],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9833891,0.0008682263,0.007940914,0.0002146195,0.00005584451,0.0008948958,0.002009406,0.00006141344,0.00456555],"genre_scores_gemma":[0.9893338,0.0001645134,0.007224944,0.000104922,0.00002338242,0.00108479,0.001624713,0.00003455325,0.0004043429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01155226,"threshold_uncertainty_score":0.06109494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5631731613126899,"score_gpt":0.4044522577820375,"score_spread":0.1587209035306524,"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."}}