{"id":"W3121131316","doi":"10.1017/asb.2018.26","title":"DRAWING DOWN RETIREMENT SAVINGS—DO PENSIONS, TAXES AND GOVERNMENT TRANSFERS MATTER MUCH FOR OPTIMAL DECISIONS?","year":2018,"lang":"en","type":"article","venue":"Astin Bulletin","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ted Rogers Centre for Heart Research","funders":"","keywords":"Economics; Social security; Government (linguistics); Risk aversion (psychology); Transfer payment; Labour economics; Public economics; Expected utility hypothesis; Financial economics; Welfare","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008190993,0.0003761193,0.0004079876,0.0001707001,0.0007425366,0.000508148,0.000304315,0.0001072056,0.005747509],"category_scores_gemma":[0.0005268767,0.0003457739,0.0001910525,0.0003082221,0.0001771126,0.0002925147,0.0003016774,0.0001383673,0.001225915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007654558,"about_ca_system_score_gemma":0.00001494034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002914318,"about_ca_topic_score_gemma":0.00007916849,"domain_scores_codex":[0.9973067,0.0000235095,0.000628025,0.0007430357,0.0007254661,0.0005732537],"domain_scores_gemma":[0.998782,0.0002323981,0.0002332781,0.0004058012,0.0003016274,0.00004494461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007090135,0.0002318937,0.3939058,0.0002133714,0.00007320062,0.00002267648,0.0003578968,0.00003055648,0.004875819,0.005315432,0.5784201,0.0158442],"study_design_scores_gemma":[0.001913877,0.0001514012,0.1473481,0.0005823305,0.0003855299,0.000004483516,0.0005564388,0.002148875,0.0007504618,0.0005336681,0.8447556,0.0008692955],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879765,0.0001213427,0.001695286,0.005693755,0.0004017132,0.0007662539,0.00003211492,0.0000864497,0.003226604],"genre_scores_gemma":[0.9824946,0.00002284322,0.009848631,0.004450707,0.001188316,0.00008586388,0.0000457676,0.00006678817,0.001796463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2663355,"threshold_uncertainty_score":0.9998994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01477099348419159,"score_gpt":0.2255751476893097,"score_spread":0.2108041542051181,"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."}}