{"id":"W2075532062","doi":"10.1002/hec.1295","title":"Does age or life expectancy better predict health care expenditures?","year":2007,"lang":"en","type":"article","venue":"Health Economics","topic":"Global Health Care Issues","field":"Health Professions","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Health Economics","funders":"National Institute on Aging","keywords":"Life expectancy; Predictive power; Health care; Censoring (clinical trials); Expectancy theory; Longevity; Gerontology; Demography; Actuarial science; Psychology; Medicine; Econometrics; Economics; Environmental health; Sociology; Population; Social psychology; Economic growth","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":[0.00279221,0.0004376284,0.0006084783,0.001159676,0.0002070094,0.0008866016,0.000501612,0.00123526,0.006755463],"category_scores_gemma":[0.01739867,0.0001662874,0.001034657,0.001000518,0.0004666334,0.001736824,0.0004817344,0.00085822,0.0009393275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002827017,"about_ca_system_score_gemma":0.000394372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006019463,"about_ca_topic_score_gemma":0.006502479,"domain_scores_codex":[0.999356,0.0003384019,0.00004632143,0.00009355224,0.00005629139,0.0001094341],"domain_scores_gemma":[0.9865369,0.007745059,0.003419719,0.0007783833,0.000469826,0.001050094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008670027,0.00005436053,0.9875937,0.00002427226,0.0001842915,0.00006008194,0.00004586031,0.001472465,0.00004224648,0.0006250626,0.0005951582,0.009215705],"study_design_scores_gemma":[0.00001518732,0.0002307125,0.9792144,0.00008603265,0.0001727856,0.0003494989,0.0002437956,0.01192311,0.0001188183,0.00545098,0.00217276,0.00002183864],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9755114,0.003841533,0.003129451,0.007801009,0.0001557253,0.00001620236,0.001769691,0.0000483242,0.007726694],"genre_scores_gemma":[0.997116,0.0008476765,0.0003681903,0.000342648,0.0001693159,0.000002635577,0.0004806879,0.000006979273,0.0006658875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006755463,"threshold_uncertainty_score":0.02259928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05510528327751662,"score_gpt":0.4373206027320131,"score_spread":0.3822153194544964,"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."}}