{"id":"W6939004064","doi":"10.6068/dp14ba8d01c7859","title":"Trend 1990 - 2011. Statistics Canada. CANSIM: Income, Pensions, Spending and Wealth - Pensions Plans and Funds and Other Retirement Income Programs | Country: Canada | Table: Pension satellite account, financial flows, by type of plan | Variable: Investment income, Individual registered saving plans (RSP) (x 1,000,000) | Units: $CAD, 1990-2011. 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; Census; Descriptive statistics; Social security; Investment (military); Official statistics; Population; Socioeconomic status; Publication; Personal income","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":[0.001874625,0.002427469,0.002775766,0.008081141,0.00311721,0.004698635,0.004878463,0.001480955,0.08237466],"category_scores_gemma":[0.01680633,0.001728743,0.00209967,0.03942421,0.0005910615,0.002478441,0.002244728,0.002987622,0.05563675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04481742,"about_ca_system_score_gemma":0.1089486,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9926906,"about_ca_topic_score_gemma":0.9915309,"domain_scores_codex":[0.9964901,0.0002180693,0.0004058843,0.0005037034,0.001573723,0.0008084834],"domain_scores_gemma":[0.9720681,0.001059458,0.0009148535,0.0008746401,0.02384674,0.001236143],"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":[0.00002196044,0.000005042598,0.0007572495,0.0002467279,0.00002005634,0.000005808924,0.00001781138,0.00008065927,0.000007891288,0.0002808136,0.9972734,0.001282474],"study_design_scores_gemma":[0.0001643949,0.00001016987,0.01965826,0.0008606085,0.00008051214,0.00002580277,0.0003547579,0.000396787,0.0001709612,0.0005888467,0.9776128,0.00007611607],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003797619,0.00004648535,0.00001447458,0.00008742385,0.00001850896,0.000008929249,0.9991645,0.0000433411,0.0005783494],"genre_scores_gemma":[0.0005205023,0.0002208785,0.0002299664,0.0001001613,0.00001404058,0.00008059588,0.9962729,0.00007427857,0.002486688],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08237466,"threshold_uncertainty_score":0.3251746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05748592661829793,"score_gpt":0.2745620739247743,"score_spread":0.2170761473064763,"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."}}