{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001925546,0.002462957,0.002705334,0.008621798,0.003214692,0.005029812,0.004841571,0.001483879,0.09882864],"category_scores_gemma":[0.01720287,0.001913633,0.00182218,0.04104166,0.000638385,0.002598408,0.002167754,0.003086985,0.06834973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04977262,"about_ca_system_score_gemma":0.1217873,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9932163,"about_ca_topic_score_gemma":0.9910666,"domain_scores_codex":[0.9957623,0.000242652,0.0004355914,0.0005818077,0.002054854,0.0009226885],"domain_scores_gemma":[0.9684989,0.001199195,0.001045917,0.001035914,0.02676676,0.001453259],"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":[0.00001959855,0.000005561716,0.0007329098,0.0001883775,0.00001658681,0.000005223015,0.00001686701,0.00009477834,0.000008625441,0.00030984,0.9973008,0.001300795],"study_design_scores_gemma":[0.0001197858,0.000008971891,0.01515807,0.0006046573,0.00004718784,0.00001867963,0.0002918839,0.0003081879,0.0001485637,0.0005226634,0.9827086,0.00006281822],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003560999,0.00003883648,0.00001768564,0.00008659754,0.00002001298,0.000009835164,0.9989634,0.00005286932,0.0007751664],"genre_scores_gemma":[0.0005384791,0.0002120591,0.0002870344,0.0001123632,0.00001360377,0.00008221046,0.9949101,0.0001025557,0.003741703],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09882864,"threshold_uncertainty_score":0.3611273,"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."}}