{"id":"W6976868491","doi":"10.6068/dp14ba8d4f4bb77","title":"Trend 1976 - 2011. Statistics Canada. CANSIM: Income, Pensions, Spending and Wealth - Low Income and Inequality | Country: Canada | Table: Persons in low income, by economic family type | Variable: Low income cut-offs before tax, 1992 base, Persons in married couples, one earnerage of persons in low income | Units: , 1976-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-121.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Race, History, and American Society","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Official statistics; Socioeconomic status; Population; Economic inequality; Census; Personal income; Demographic statistics; Inequality; Poverty","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":[0.003239095,0.001163543,0.002587392,0.0005200781,0.0005943016,0.0002378777,0.002322718,0.0009050868,0.002176105],"category_scores_gemma":[0.0003360905,0.00128294,0.000002051222,0.0008978465,0.001749229,0.0006671103,0.0009923627,0.002054157,0.00002420529],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002782403,"about_ca_system_score_gemma":0.02659765,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9997555,"about_ca_topic_score_gemma":0.9996678,"domain_scores_codex":[0.9912529,0.001693191,0.00188085,0.002003541,0.001496719,0.001672793],"domain_scores_gemma":[0.9931121,0.001654006,0.001614788,0.002248856,0.00008161482,0.001288596],"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":[0.0001564136,0.0001800211,0.01511657,0.001280247,0.000165247,0.0003646233,0.0002972606,0.00003300262,0.00000438291,0.000322964,0.9820025,0.00007677863],"study_design_scores_gemma":[0.001923909,0.0001503692,0.00146592,0.0004658333,0.0001603864,0.00002580751,0.007600814,0.003784164,2.007261e-8,0.000001191199,0.9830945,0.001327142],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001484578,0.003179652,0.000003861991,0.00002245262,0.0008082654,0.001206668,0.9917172,0.00006124267,0.001516117],"genre_scores_gemma":[0.01018314,0.003581622,0.000271086,0.0002503395,0.0002152183,0.00003285163,0.9830317,0.0002430262,0.002190943],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02381525,"threshold_uncertainty_score":0.998962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02410398438427057,"score_gpt":0.261322580083406,"score_spread":0.2372185956991354,"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."}}