{"id":"W6901690359","doi":"10.6068/dp14ba83aab8c32","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: All employees, Plans, Defined benefit 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":"Advanced Data and IoT Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Descriptive statistics; Payroll; Pension; Census; Wages and salaries; Socioeconomic status; Social security; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004218009,0.001001326,0.001587628,0.0001652514,0.000166607,0.0001419393,0.001638058,0.0007639764,0.0001559551],"category_scores_gemma":[0.0002693905,0.0008559031,6.733071e-7,0.000317664,0.0003382245,0.000297059,0.0006044314,0.0007620495,0.000002052249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002078166,"about_ca_system_score_gemma":0.00249674,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9932278,"about_ca_topic_score_gemma":0.9977081,"domain_scores_codex":[0.9954784,0.0001206096,0.001274287,0.001163314,0.000895026,0.001068393],"domain_scores_gemma":[0.9936609,0.0017898,0.0008759144,0.003086281,0.0001675057,0.0004195551],"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":[0.0005333456,0.0000490026,0.0001236886,0.001378261,0.0005507008,0.0001200886,0.000007302503,0.0003681048,0.00006837461,0.0007449795,0.9959376,0.0001185493],"study_design_scores_gemma":[0.001944676,0.0003324895,0.00001672429,0.0002178595,0.0006258372,0.0001053406,0.0002541655,0.002616345,0.000002434717,0.000001291519,0.9929375,0.0009453019],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002241809,0.01489865,0.00004788418,0.000007135845,0.0007134888,0.001050046,0.9827653,0.000205852,0.0002892665],"genre_scores_gemma":[0.0001005865,0.01272348,0.0004102229,0.0001152024,0.00009959402,0.00002599667,0.9855518,0.000297199,0.0006759252],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.004480356,"threshold_uncertainty_score":0.9993892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03857648817839217,"score_gpt":0.2493760633315656,"score_spread":0.2107995751531734,"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."}}