{"id":"W2016192448","doi":"10.1007/s11136-007-9256-7","title":"The predictive validity of health-related quality of life measures: mortality in a longitudinal population-based study","year":2007,"lang":"en","type":"article","venue":"Quality of Life Research","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":106,"is_retracted":false,"has_abstract":false,"ca_institutions":"Statistics Canada; Institute of Health Economics; Utilities Kingston (Canada); University of Alberta; Canadian Institute for Health Information","funders":"National Institute on Aging; Health Canada","keywords":"Confounding; Medicine; Confidence interval; Demography; Health Utilities Index; National Death Index; Predictive validity; Proportional hazards model; Gerontology; Population; Longitudinal study; Environmental health; Health related quality of life; Hazard ratio; Internal medicine; Clinical psychology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.4541327,0.0002873601,0.003083998,0.0009680997,0.0004717773,0.00004063894,0.0009231569,0.0002936454,0.0001097144],"category_scores_gemma":[0.09462599,0.0003022943,0.0003593422,0.001523828,0.0006018443,0.0003147692,0.0001660698,0.000822825,0.00003757187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001143306,"about_ca_system_score_gemma":0.002060541,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1742152,"about_ca_topic_score_gemma":0.03130006,"domain_scores_codex":[0.942312,0.0239181,0.0285946,0.001343813,0.002341655,0.001489815],"domain_scores_gemma":[0.9608199,0.02586842,0.009745198,0.001853491,0.001197602,0.0005153854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004988824,0.001521281,0.9705772,0.001330974,0.0002217221,3.004612e-7,0.003408253,0.0005938617,0.000003245636,0.02150722,0.0002208442,0.0001162198],"study_design_scores_gemma":[0.002152272,0.0005033067,0.9758391,0.0001289704,0.000004821107,9.453155e-8,0.00977697,0.0007134186,0.000009454859,0.01059943,0.00005501553,0.0002171767],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9857947,0.002413447,0.001657156,0.00619034,0.0002527232,0.002792328,0.0004782017,0.00002915157,0.000391957],"genre_scores_gemma":[0.9992067,0.0000672465,0.0002117871,0.0002166998,0.00009122257,0.00009296423,0.00004609798,0.00003216687,0.00003512872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3595067,"threshold_uncertainty_score":0.9999429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8125122992185508,"score_gpt":0.582330966469696,"score_spread":0.2301813327488549,"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."}}