{"id":"W6976698538","doi":"10.6068/dp14ba8d2a23932","title":"Trend 1999 - 2006. 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: Furniture and related product manufacturing, Members, females, Defined contribution registered pension plans, Number | Units: #, 1999-2006. 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; Wages and salaries; Economic statistics; Summary statistics; Official statistics; Social security","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":[0.001557364,0.00237346,0.002589951,0.008460682,0.002966251,0.004387789,0.004713609,0.001441786,0.07923286],"category_scores_gemma":[0.01545329,0.001533013,0.001844674,0.03861291,0.0005782168,0.00218112,0.001987071,0.002701291,0.05170992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04250521,"about_ca_system_score_gemma":0.09828582,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9923436,"about_ca_topic_score_gemma":0.9910209,"domain_scores_codex":[0.9965637,0.0001955965,0.0003716604,0.000527307,0.001542558,0.0007991154],"domain_scores_gemma":[0.9742383,0.001072313,0.0009736395,0.0008715754,0.02161445,0.001229748],"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":[0.00002075877,0.000005231572,0.0008301052,0.0001887889,0.00001778369,0.000005809331,0.00001538091,0.00009790288,0.000008102709,0.0003159843,0.9973927,0.001101456],"study_design_scores_gemma":[0.0001439225,0.000009562254,0.01825682,0.000679128,0.00006003349,0.00002472622,0.0003522324,0.0004499391,0.0001739729,0.0005868647,0.9791917,0.00007100072],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003578172,0.00003390725,0.00001197928,0.00006816071,0.00001476044,0.000006198263,0.9992831,0.00003678391,0.0005092493],"genre_scores_gemma":[0.0005129254,0.0001482789,0.0001836199,0.00008000274,0.00000946646,0.00005231035,0.9967925,0.00005450274,0.002166439],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07923286,"threshold_uncertainty_score":0.3083984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02887335216746149,"score_gpt":0.2448526853894851,"score_spread":0.2159793332220236,"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."}}