{"id":"W6920415718","doi":"10.6068/dp14ba8b2771312","title":"Trend 1990 - 2012. 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: Provincial government, public sector, Members, males, Contributory registered pension plans, Number | Units: #, 1990-2012. 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; Descriptive statistics; Census; Summary statistics; Social security; Economic statistics; 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":[0.001862092,0.002393676,0.002738403,0.008469059,0.003117162,0.004828629,0.004886745,0.001530088,0.07984168],"category_scores_gemma":[0.01754515,0.001732356,0.001912253,0.04055198,0.0006178318,0.002488084,0.002138237,0.003056254,0.05491235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04607274,"about_ca_system_score_gemma":0.1126463,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9929784,"about_ca_topic_score_gemma":0.9916595,"domain_scores_codex":[0.9961808,0.0002222106,0.0004202671,0.0005587803,0.001742441,0.0008755277],"domain_scores_gemma":[0.9711863,0.001146872,0.001037759,0.0009486566,0.02424224,0.001438109],"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":[0.00002054978,0.000005314784,0.0007755317,0.0002036451,0.00001782621,0.000005338467,0.00001820051,0.0000804363,0.000007592514,0.0002801859,0.9974602,0.001125078],"study_design_scores_gemma":[0.0001682618,0.00001021244,0.01912399,0.0007489453,0.00006574651,0.00002385047,0.0003622358,0.0003779595,0.0001609582,0.000594098,0.9782909,0.00007269616],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003798991,0.00003835742,0.00001297831,0.00008442443,0.00001593252,0.000008139512,0.9992053,0.00004413636,0.0005527684],"genre_scores_gemma":[0.0005248604,0.0001750018,0.000217435,0.00009995369,0.00001265212,0.000075968,0.9963708,0.00007672806,0.002446665],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07984168,"threshold_uncertainty_score":0.3342826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02761911917023002,"score_gpt":0.2408630283331866,"score_spread":0.2132439091629565,"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."}}