{"id":"W3210888774","doi":"10.1136/oem-2021-epi.3","title":"O-331 Understanding age differences in retirement expectations using data from the Canadian Longitudinal Study on Aging","year":2021,"lang":"en","type":"article","venue":"Oral Presentations","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Psychosocial; Gerontology; Retirement age; Population ageing; Association (psychology); Psychology; Successful aging; Longitudinal study; Health and Retirement Study; Population; Demography; Medicine; Economics; Pension; Finance; Environmental health","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0004272693,0.0000961763,0.0001229334,0.00006673569,0.001769089,0.0004693412,0.0004245295,0.00003031861,0.0003878201],"category_scores_gemma":[0.0003013187,0.00008336999,0.00002949143,0.0004640864,0.0002082327,0.0002812813,0.0001165153,0.0001335584,0.00001253111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007180067,"about_ca_system_score_gemma":0.0004935515,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.754321,"about_ca_topic_score_gemma":0.9937935,"domain_scores_codex":[0.9979465,0.0006115555,0.0002270166,0.0003759289,0.0005294338,0.0003095836],"domain_scores_gemma":[0.9989449,0.0003581166,0.00005211122,0.0004755869,0.0000442604,0.0001250183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002149807,0.0001771845,0.9509013,0.000001393111,0.00003228982,0.0000245082,0.04223531,0.00004461252,0.00001005847,0.005822727,0.0007043718,0.00004410842],"study_design_scores_gemma":[0.0002015479,0.00001320045,0.6347938,0.00002332812,0.00003704428,6.938625e-8,0.3597165,0.0002843219,0.000004520291,0.004713872,0.0001175037,0.00009425772],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817705,0.00005042239,0.0004006414,0.00691213,0.0003698736,0.0006100931,0.00008901142,0.00002260974,0.009774778],"genre_scores_gemma":[0.9992998,0.000009940758,0.0001690868,0.00008347365,0.0001186127,0.00002621339,0.0001290643,0.000007036796,0.0001567196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3174812,"threshold_uncertainty_score":0.9995305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8342274191263048,"score_gpt":0.5442226096721479,"score_spread":0.290004809454157,"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."}}