{"id":"W6939132673","doi":"10.6068/dp14ba8e26e2a92","title":"Trend 1974 - 2012. Statistics Canada. CANSIM: Income, Pensions, Spending and Wealth - Pensions Plans and Funds and Other Retirement Income Programs | Country: Canada | Table: Registered pension plans (RPPs), members and market value of assets, by type of plan, sector and contributory status | Variable: Members, both sexes, Contributory registered pension plans, Total defined benefit plans | Units: # %, 1974-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-122.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pension; Census; Descriptive statistics; Social security; Official statistics; Socioeconomic status; Population; Publication; Personal income; Summary statistics","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":[0.001689969,0.002345397,0.002847147,0.008648142,0.002882581,0.00474921,0.004667313,0.00132585,0.08230057],"category_scores_gemma":[0.01691585,0.001675345,0.001952365,0.04245053,0.0005880279,0.002358532,0.002097863,0.00286456,0.05734503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04621746,"about_ca_system_score_gemma":0.1078731,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9929576,"about_ca_topic_score_gemma":0.9918708,"domain_scores_codex":[0.9963796,0.0002008188,0.0004227388,0.0005338051,0.001657704,0.000805466],"domain_scores_gemma":[0.9697,0.001157359,0.001064874,0.0009747609,0.02574733,0.001355703],"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":[0.0000215414,0.000005542535,0.0008885554,0.0002062211,0.00002000628,0.000005442257,0.00001806286,0.00008641496,0.000008491468,0.0002878637,0.9972013,0.001250544],"study_design_scores_gemma":[0.0001610114,0.00001007862,0.02106367,0.0007217521,0.00006713357,0.00002181125,0.0003897814,0.0003949755,0.000178711,0.0005401053,0.9763798,0.00007115721],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004444475,0.00003874629,0.0000142629,0.00007220476,0.0000163456,0.000008502741,0.9991292,0.00004838504,0.0006278711],"genre_scores_gemma":[0.0005369937,0.0001731643,0.0002095544,0.00008013526,0.00001225428,0.00007030288,0.9960772,0.00006860799,0.002771677],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08230057,"threshold_uncertainty_score":0.3353327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04087348265812922,"score_gpt":0.2678994235175668,"score_spread":0.2270259408594376,"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."}}