{"id":"W2159949990","doi":"10.1017/s0144686x99007904","title":"Poor health and retirement income: the Canadian case","year":2000,"lang":"en","type":"article","venue":"Ageing and Society","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Pension; Demographic economics; Disadvantaged; Health and Retirement Study; Social security; Dividend; Economics; Human capital; Gerontology; Economic growth; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001826246,0.0005792453,0.0005883595,0.003828737,0.01142174,0.001860806,0.001527062,0.00145828,0.003925819],"category_scores_gemma":[0.006943214,0.0004764443,0.0006582365,0.01060526,0.002080545,0.0008476102,0.002489919,0.001612587,0.0002667211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03618734,"about_ca_system_score_gemma":0.04137768,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9907966,"about_ca_topic_score_gemma":0.9950122,"domain_scores_codex":[0.9979412,0.000205036,0.00004808803,0.0001217924,0.0005213165,0.00116262],"domain_scores_gemma":[0.9975859,0.0003033664,0.0004125865,0.00018343,0.0007432123,0.0007715177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000191705,0.000240467,0.9019821,0.0001273418,0.00008315138,0.008895466,0.01071419,0.0005692935,0.0001320362,0.0222393,0.02129799,0.03352708],"study_design_scores_gemma":[0.00006057073,0.00007409266,0.9403532,0.0003476842,0.0001591088,0.006145656,0.02242599,0.002362574,0.00007382563,0.003429196,0.0244611,0.0001069536],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9363266,0.005077131,0.000236483,0.008875001,0.0001256636,0.000137591,0.003269682,0.00001252813,0.0459393],"genre_scores_gemma":[0.9923458,0.003721472,0.0003056179,0.0004581509,0.00004036521,0.00003961677,0.0006533797,0.000005065784,0.002430476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03618734,"threshold_uncertainty_score":0.2625587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1161622551479346,"score_gpt":0.3895389153097223,"score_spread":0.2733766601617876,"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."}}