{"id":"W2828500297","doi":"10.1093/geront/gnw162.728","title":"RETIREMENT SECURITY AMONG THE NEVER MARRIED POPULATION","year":2016,"lang":"en","type":"article","venue":"The Gerontologist","topic":"Migration, Aging, and Tourism Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Institute for Work & Health","funders":"","keywords":"Population; Psychology; Demographic economics; Demography; Gerontology; Sociology; Medicine; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009472802,0.00007367998,0.00008572796,0.000009460356,0.00126523,0.00004408695,0.0002657019,0.00004398238,0.0002106399],"category_scores_gemma":[0.0002332758,0.00002980902,0.0000450472,0.00007602747,0.0006594048,0.0001578401,0.00004317141,0.00005296433,0.00003077326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008696321,"about_ca_system_score_gemma":0.00002085759,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08352391,"about_ca_topic_score_gemma":0.3134304,"domain_scores_codex":[0.9989431,0.0003227101,0.0001315142,0.0001308228,0.0002505427,0.0002212902],"domain_scores_gemma":[0.9994207,0.0001756481,0.000100464,0.0002285897,0.00004523722,0.00002933599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000321608,0.00003222029,0.4446214,0.000004612538,0.00004229101,0.00000187765,0.312166,0.000001337311,0.00002125479,0.1509096,0.08580808,0.006359151],"study_design_scores_gemma":[0.0001118568,0.00001035909,0.9369061,0.000007801174,0.00001673656,1.25196e-7,0.001706631,0.000005924438,0.00001330582,0.02023011,0.04091651,0.00007456217],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9578884,0.0003066598,0.000238523,0.02671784,0.0004090343,0.0002937177,0.000003226423,0.00008599965,0.01405658],"genre_scores_gemma":[0.9935725,0.0001789985,0.00001119711,0.0002340983,0.0003481147,0.00002470207,0.000001094145,0.000003553326,0.005625751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4922847,"threshold_uncertainty_score":0.9731255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02573662497378593,"score_gpt":0.2973703711209839,"score_spread":0.2716337461471979,"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."}}