{"id":"W6920467845","doi":"10.6068/dp14ba8edabbe88","title":"Trend 1976 - 2011. Statistics Canada. CANSIM: Income, Pensions, Spending and Wealth - Household, Family and Personal Income | Country: Canada | Table: Persons in low income families | Variable: Low income cut-offs after tax, 1992 base, Persons 65 years and over, Aggregate low income gap as a percentage of income | 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":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Personal income; Socioeconomic status; Total personal income; Official statistics; Economic statistics; Population; Household income; Census; Distribution (mathematics); 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":[0.002214079,0.002389984,0.002836272,0.007982491,0.003386103,0.004868076,0.005787543,0.001577658,0.08565973],"category_scores_gemma":[0.01954818,0.001822122,0.002171442,0.03821355,0.0006399393,0.002526092,0.002520223,0.003522245,0.05332046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04867118,"about_ca_system_score_gemma":0.1140996,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9930208,"about_ca_topic_score_gemma":0.9916433,"domain_scores_codex":[0.9962112,0.0002601877,0.0004264022,0.000508426,0.001700094,0.0008936644],"domain_scores_gemma":[0.9667515,0.001328841,0.001045325,0.001123188,0.02819377,0.001557507],"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":[0.000021555,0.000006004566,0.0009510153,0.0002174735,0.00001971484,0.000005693761,0.00002058633,0.00009822576,0.000007539663,0.0003373104,0.9969348,0.001380157],"study_design_scores_gemma":[0.0001752818,0.00001206277,0.02420113,0.000947309,0.00007054688,0.00002781436,0.0004430857,0.0004730478,0.0001792334,0.0007544571,0.9726183,0.00009776491],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004379911,0.00003585281,0.00001965269,0.00008776382,0.00001853084,0.00001289813,0.9991652,0.00004858117,0.000567735],"genre_scores_gemma":[0.0005657609,0.0001796541,0.0002937963,0.00009750087,0.00001237142,0.0001106599,0.9961831,0.00007963832,0.002477584],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08565973,"threshold_uncertainty_score":0.3531358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0221315959413643,"score_gpt":0.2453173097396731,"score_spread":0.2231857137983088,"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."}}