{"id":"W6957637683","doi":"10.6068/dp14ba86db32e43","title":"Trend 1999 - 2009. Statistics Canada. CANSIM: Labor - Nonwage Benefits | Country: Canada | Table: Registered pension plans (RPPs), members and market value of assets, by North American Industry Classification System (NAICS), sector, type of plan and contributory status | Variable: Clothing manufacturing, Plans, Defined contribution registered pension plans | Units: # %, 1999-2009. 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; Descriptive statistics; Pension; Census; Wages and salaries; Economic statistics; Official statistics; Summary statistics; Social security; Value (mathematics)","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":[0.001760674,0.002369413,0.002631888,0.007725048,0.003065258,0.00487248,0.005034546,0.001551829,0.08905289],"category_scores_gemma":[0.01652673,0.00166985,0.001912557,0.03628176,0.0005934516,0.00246103,0.002149173,0.002990952,0.06336402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04099337,"about_ca_system_score_gemma":0.0963996,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9908014,"about_ca_topic_score_gemma":0.9889134,"domain_scores_codex":[0.9963231,0.0002136547,0.0004097128,0.0005494549,0.001689001,0.0008150295],"domain_scores_gemma":[0.9722207,0.00112274,0.0009338539,0.0009580193,0.0235303,0.001234398],"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":[0.00001952442,0.000005140923,0.0006740435,0.0001691042,0.00001603831,0.000005180103,0.00001329383,0.00007996522,0.000007452707,0.0002565037,0.9977587,0.0009948701],"study_design_scores_gemma":[0.000154269,0.000009028564,0.01612917,0.0006862291,0.00005498103,0.00002150529,0.0003072901,0.0003686567,0.0001667887,0.0005553493,0.9814787,0.00006798113],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003089102,0.00003004678,0.00001156282,0.00007279776,0.0000171818,0.000007039371,0.9992593,0.00003769897,0.0005334642],"genre_scores_gemma":[0.0004022871,0.0001359849,0.0001713397,0.00008669067,0.00001086544,0.00005971274,0.9966929,0.00006289636,0.002377321],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08905289,"threshold_uncertainty_score":0.2979116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03168325470862732,"score_gpt":0.2467266004889953,"score_spread":0.2150433457803679,"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."}}