{"id":"W6976972463","doi":"10.6068/dp14ba8b5a87e55","title":"Trend 1976 - 2011. Statistics Canada. CANSIM: Income, Pensions, Spending and Wealth - Household, Family and Personal Income | Country: Canada | Table: Average total income, by census family type and living arrangement, 2011 constant dollars | Variable: Non-elderly females not in families, Average income of those living on their own | 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":"Academic Research in Diverse Fields","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Personal income; Economic statistics; Socioeconomic status; Population; Demographic statistics; Official statistics; Household income; Standard of living; Total 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002910817,0.0008591183,0.001418638,0.0003530032,0.0005492307,0.0002988275,0.001715847,0.0008023546,0.001210961],"category_scores_gemma":[0.0005370891,0.0008126558,6.596147e-7,0.0003982466,0.0009974524,0.000500261,0.001895212,0.001855912,0.00001028161],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000571731,"about_ca_system_score_gemma":0.01074792,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9990755,"about_ca_topic_score_gemma":0.9919804,"domain_scores_codex":[0.9930102,0.001181114,0.001122498,0.001423346,0.001969857,0.00129302],"domain_scores_gemma":[0.992582,0.004180943,0.0009081577,0.001232397,0.0001223553,0.0009741394],"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":[0.0001207364,0.00005609705,0.004210388,0.0006634494,0.0001993106,0.0003892268,0.0001260466,0.000007525163,0.00001605982,0.0003756459,0.9935867,0.0002487919],"study_design_scores_gemma":[0.0007765549,0.0001989865,0.001149034,0.0005142537,0.0001071465,0.00004425416,0.004627894,0.0008654575,2.570932e-8,7.778924e-7,0.9908432,0.0008723743],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008317559,0.004384749,0.000004986675,0.000007545716,0.0006387658,0.0009411337,0.9891863,0.00004832919,0.003956456],"genre_scores_gemma":[0.009634626,0.02167829,0.0001566285,0.0002004964,0.000161922,0.00001100664,0.9665097,0.0001554334,0.001491887],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02267657,"threshold_uncertainty_score":0.9997021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05711046180368495,"score_gpt":0.288469690705623,"score_spread":0.2313592289019381,"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."}}