{"id":"W3125354850","doi":"","title":"Private financing of long-term care: income, savings and reverse mortgages","year":2019,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Global Health Care Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Long-term care; Equity (law); Home equity; Residence; Business; Actuarial science; Long-term care insurance; Health care; Demographic economics; Older people; Finance; Economics; Public economics; Economic growth; Medicine","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":[0.00101792,0.000401149,0.0006806394,0.0004185784,0.0003285529,0.001871696,0.0006525441,0.00137568,0.004477661],"category_scores_gemma":[0.004085535,0.0003624192,0.0007972809,0.0006787162,0.0007158458,0.001731049,0.0008591671,0.0009683016,0.0003601388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001434822,"about_ca_system_score_gemma":0.00146144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04694567,"about_ca_topic_score_gemma":0.0304171,"domain_scores_codex":[0.9996866,0.0001103578,0.00001433449,0.00005955793,0.00002896944,0.0001002678],"domain_scores_gemma":[0.998204,0.0008928989,0.0005184308,0.00007140783,0.0001415026,0.000171729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002695149,0.0002333899,0.1348394,0.00008536228,0.0001760485,0.0003619494,0.0001816555,0.8075199,0.0004385362,0.04451277,0.002179762,0.00920184],"study_design_scores_gemma":[0.0001421755,0.0002842075,0.04229194,0.0001014974,0.0001496295,0.0001392163,0.0006691458,0.9249758,0.0006252347,0.02707935,0.003492783,0.0000489938],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813882,0.0006518519,0.01030197,0.002230186,0.00002982004,0.00003020189,0.001092467,0.00004011114,0.004235135],"genre_scores_gemma":[0.9942572,0.0003390368,0.001438717,0.00008097201,0.00001816001,0.00002567166,0.0005844638,0.000008990226,0.003246784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04694567,"threshold_uncertainty_score":0.09334481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04772430292332247,"score_gpt":0.4319222032369098,"score_spread":0.3841979003135874,"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."}}