{"id":"W6957743162","doi":"10.6068/dp14ba8dd5a5e59","title":"Trend 1976 - 2011. Statistics Canada. CANSIM: Income, Pensions, Spending and Wealth - Household, Family and Personal Income | Country: Canada | Table: Government transfers, by economic family type and after-tax income quintiles, 2011 constant dollars | Variable: Lowest quintile, Average implicit rates of government transfers, Economic families, two persons or more | Units: , 1976-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-119.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Healthcare Systems and Public Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Personal income; Socioeconomic status; Government (linguistics); Total personal income; Census; Population; Family income; Transfer payment; 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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001417012,0.001218795,0.002541948,0.0001441953,0.0002725082,0.0001785,0.0008139358,0.0006173013,0.002213204],"category_scores_gemma":[0.00003738452,0.001102456,0.000001232317,0.0001308194,0.0005429531,0.0003266729,0.00041555,0.001126548,0.0000143567],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002093084,"about_ca_system_score_gemma":0.02902599,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9995109,"about_ca_topic_score_gemma":0.9976102,"domain_scores_codex":[0.9930681,0.0005349289,0.001940462,0.001805465,0.001360026,0.001291044],"domain_scores_gemma":[0.9944865,0.0008913554,0.0007769677,0.001831035,0.00005749374,0.001956713],"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":[0.000939826,0.00007368027,0.002702018,0.00344746,0.0005897093,0.0005332961,0.00003199534,0.000003502446,0.00001424931,0.0002191756,0.991151,0.0002940543],"study_design_scores_gemma":[0.003390798,0.0007464029,0.0007516111,0.0003388794,0.0005127823,0.0006134164,0.00276565,0.001171825,6.062328e-8,1.372474e-7,0.9886647,0.001043742],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001361021,0.007303503,0.000007854881,0.00004089661,0.0009254417,0.001825321,0.9878755,0.00004638484,0.0006140298],"genre_scores_gemma":[0.007236787,0.01894933,0.0001251192,0.0006208864,0.0002152664,0.00003301864,0.9711924,0.0003114794,0.00131576],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02693291,"threshold_uncertainty_score":0.9991426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02555141237588902,"score_gpt":0.2639047195570916,"score_spread":0.2383533071812026,"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."}}