{"id":"W6901599116","doi":"10.6068/dp14ba83e37c259","title":"Trend 1974 - 2006. Statistics Canada. CANSIM: Labor - Nonwage Benefits | Country: Canada | Table: Registered pension plans (RPPs) and members, by class of employees eligible for the plan, sector, type of plan and contributory status | Variable: Executives, Members, females, Total of registered pension plans | Units: # %, 1974-2006. 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":"Descriptive statistics; Pension; Payroll; Census; Wages and salaries; Social security; Socioeconomic status; Summary statistics; Economic statistics; Official 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":[0.001949776,0.002478467,0.002722221,0.008564511,0.003158105,0.004987395,0.004823446,0.001503767,0.09948875],"category_scores_gemma":[0.0178475,0.001933747,0.001840558,0.04081901,0.0006423383,0.002564713,0.00219465,0.003112582,0.07077632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04698389,"about_ca_system_score_gemma":0.1180029,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9925862,"about_ca_topic_score_gemma":0.9903182,"domain_scores_codex":[0.9957582,0.000249244,0.0004453371,0.0005873303,0.002025519,0.000934258],"domain_scores_gemma":[0.9684731,0.001262516,0.001048012,0.001070858,0.02666336,0.0014821],"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":[0.00001837572,0.000005329093,0.0006749518,0.0001736893,0.00001551731,0.000004997185,0.00001597191,0.00008761042,0.000007999573,0.0002831208,0.99753,0.001182454],"study_design_scores_gemma":[0.0001258459,0.00000904938,0.01463932,0.0005969732,0.00004667086,0.00001897578,0.0002878144,0.0003092802,0.0001506162,0.0005396381,0.9832125,0.0000632722],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003320067,0.00003481767,0.00001697415,0.00008247974,0.00001946777,0.000009385019,0.9990202,0.00005394353,0.0007294596],"genre_scores_gemma":[0.0004841509,0.0001879737,0.0002757238,0.0001075403,0.00001323977,0.00007963142,0.9953142,0.0001033666,0.003434091],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09948875,"threshold_uncertainty_score":0.3408936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05057466102085056,"score_gpt":0.2681265289413241,"score_spread":0.2175518679204735,"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."}}