{"id":"W7071703840","doi":"","title":"Three Papers on Retirement and Canada's Public Pension System","year":2022,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"QR Code Applications and Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Receipt; Earnings; Pension; Sample (material); Pension system; Public policy; Longitudinal data; Labour supply; Panel data","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":[0.001670791,0.0006356679,0.0005298217,0.00449537,0.007638989,0.006942096,0.001349047,0.001989969,0.02374901],"category_scores_gemma":[0.005919739,0.0003659138,0.0008780223,0.01181267,0.002535696,0.001859686,0.002092397,0.002225902,0.001916226],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05482264,"about_ca_system_score_gemma":0.07038371,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9099791,"about_ca_topic_score_gemma":0.9535756,"domain_scores_codex":[0.9983957,0.0001220446,0.00004844497,0.0001525106,0.000807611,0.000473604],"domain_scores_gemma":[0.9958054,0.001013479,0.000320265,0.0002004085,0.001926536,0.0007339229],"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":[0.0000737737,0.00007695107,0.01235624,0.001351553,0.00006534914,0.0003055613,0.004987826,0.001623012,0.000401418,0.3090395,0.5277973,0.1419215],"study_design_scores_gemma":[0.000009832254,0.00001120186,0.01393281,0.001239629,0.00002326346,0.00005860225,0.002256993,0.000222745,0.0001719536,0.009390548,0.9726465,0.00003599928],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.02991045,0.2595203,0.004849366,0.1311618,0.01311617,0.0001749215,0.005769647,0.000244059,0.5552533],"genre_scores_gemma":[0.20042,0.3081602,0.005374601,0.03721272,0.00786043,0.0002341907,0.004183279,0.0002828897,0.4362717],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9451774,"threshold_uncertainty_score":0.397768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01360802893270245,"score_gpt":0.1849061625149059,"score_spread":0.1712981335822035,"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."}}