{"id":"W6977094154","doi":"10.6068/dp14ba7ca792135","title":"Trend 2000 - 2011. Statistics Canada. CANSIM: Labor - Employment Insurance, Social Assistance and Other Transfers | Country: Canada | Table: Economic dependency profile, by sex, taxfilers and income, and source of income | Variable: Canada Child Tax Benefit, Both sexes, Amount of income | Units: $CAD x 1,000, 2000-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-137.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Historical Architecture and Urbanism","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Economic statistics; Official statistics; Social statistics; Population; Summary statistics; Social insurance; Social security; Population statistics; Government (linguistics)","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":[0.002097951,0.002473768,0.002743311,0.008365041,0.003031015,0.004822796,0.005462862,0.001650755,0.1087795],"category_scores_gemma":[0.02013715,0.001949849,0.002091959,0.0385078,0.0006309518,0.002624689,0.002480746,0.003261364,0.06694859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04480183,"about_ca_system_score_gemma":0.109099,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9908617,"about_ca_topic_score_gemma":0.9885932,"domain_scores_codex":[0.9960595,0.0002702692,0.0004664758,0.0005543865,0.001747286,0.0009020862],"domain_scores_gemma":[0.9696173,0.001420818,0.001091837,0.001140883,0.02521987,0.001509264],"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":[0.00001978089,0.000005430684,0.000685617,0.0001969388,0.00001599126,0.00000527637,0.00001559306,0.00009476301,0.000006971541,0.0002932405,0.9975066,0.001153947],"study_design_scores_gemma":[0.0001793598,0.0000103942,0.01724739,0.0008552191,0.00006142934,0.00002453405,0.0003502204,0.0004801345,0.0001649012,0.0007367511,0.979807,0.00008277195],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000323785,0.00002972791,0.00001664997,0.00008437406,0.00001698037,0.000009460967,0.9991702,0.0000487829,0.0005914638],"genre_scores_gemma":[0.0004708041,0.0001660877,0.0002570909,0.0001033442,0.00001147127,0.00009662161,0.9961707,0.0000931824,0.002630702],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1087795,"threshold_uncertainty_score":0.3639035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01147743908308221,"score_gpt":0.1977672311490994,"score_spread":0.1862897920660172,"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."}}