{"id":"W6976888320","doi":"10.6068/dp14ba8ab49ce44","title":"Trend 1980 - 2006. Statistics Canada. CANSIM: Labor - Nonwage Benefits | Country: Canada | Table: Registered pension plans (RPPs), members and market value of assets, by type of organization, type of plan and contributory status | Variable: Federal enterprise, public sector, Members, both sexes, Defined benefit registered pension plans | Units: # %, 1980-2006. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-142.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Payroll; Pension; Census; Descriptive statistics; Summary statistics; Economic statistics; Social security; Wages and salaries; Value (mathematics); Socioeconomic status","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":[0.001789947,0.002364532,0.002543053,0.008803025,0.003193228,0.0046591,0.004669482,0.001460134,0.08292075],"category_scores_gemma":[0.01631317,0.001748206,0.001704325,0.04017007,0.0006252746,0.002426959,0.00202415,0.002987612,0.05679329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04841162,"about_ca_system_score_gemma":0.1169886,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9930092,"about_ca_topic_score_gemma":0.9915596,"domain_scores_codex":[0.9961656,0.0002103503,0.0003965911,0.0005370877,0.001820594,0.0008696788],"domain_scores_gemma":[0.969863,0.001143495,0.001080154,0.0009325385,0.02553278,0.001447925],"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":[0.00001939959,0.000005590307,0.000782042,0.0001869776,0.0000157556,0.000005115543,0.00001785386,0.00008775071,0.000008120929,0.0003187298,0.9973956,0.001157091],"study_design_scores_gemma":[0.0001293287,0.000009243024,0.01798813,0.0006267147,0.00005017532,0.00002014554,0.0003313235,0.0003279511,0.0001587171,0.0005092512,0.9797843,0.00006465455],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003990524,0.00003625598,0.00001327761,0.00007735421,0.00001668465,0.000008439231,0.9991038,0.00004364186,0.0006605967],"genre_scores_gemma":[0.000535129,0.0001813,0.0002186502,0.00009318136,0.00001218092,0.00007328963,0.9957729,0.00007535191,0.003038086],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08292075,"threshold_uncertainty_score":0.3512526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02755563789830978,"score_gpt":0.2391871299906689,"score_spread":0.2116314920923592,"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."}}