{"id":"W6901611949","doi":"10.6068/dp14ba8f5bc7480","title":"Trend 1999 - 2012. Statistics Canada. CANSIM: Income, Pensions, Spending and Wealth - Pensions Plans and Funds and Other Retirement Income Programs | 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: Beverage and tobacco product manufacturing, Members, males, Non-contributory registered pension plans, Number | Units: #, 1999-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-122.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pension; Descriptive statistics; Census; Social security; Population; Official statistics; Socioeconomic status; Publication; Personal income; Summary 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":[0.001693186,0.002421612,0.003131374,0.007437404,0.00285552,0.004739503,0.005260834,0.001518077,0.07150374],"category_scores_gemma":[0.01539798,0.001702872,0.002207283,0.03741877,0.0005537244,0.002304513,0.002126696,0.003147129,0.05249951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03997867,"about_ca_system_score_gemma":0.09365015,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9905719,"about_ca_topic_score_gemma":0.9894923,"domain_scores_codex":[0.9966085,0.0002070773,0.0004089809,0.0005070606,0.00147507,0.000793324],"domain_scores_gemma":[0.9731544,0.001005811,0.0009864644,0.0008798296,0.02274045,0.0012331],"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":[0.00002785207,0.000006671211,0.001044572,0.0002296203,0.00002312819,0.000006290531,0.00001741051,0.00009129154,0.000008146191,0.000258771,0.9971168,0.001169482],"study_design_scores_gemma":[0.0002375251,0.00001417604,0.02708232,0.000934019,0.00009044637,0.0000295358,0.0004647241,0.000521799,0.0001993382,0.0006485993,0.9696904,0.00008718465],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004932113,0.00004074882,0.00001232989,0.00007881824,0.00001978666,0.000008612777,0.9992699,0.00003865272,0.0004817693],"genre_scores_gemma":[0.0005168722,0.0001556702,0.0001562756,0.00008710889,0.00001315377,0.00006927238,0.9968824,0.00005184468,0.002067399],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07150374,"threshold_uncertainty_score":0.2900669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04116944973944198,"score_gpt":0.2691156319837771,"score_spread":0.2279461822443351,"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."}}