{"id":"W6938797455","doi":"10.6068/dp14ba7b9103267","title":"Trend 2000 - 2006. Statistics Canada. CANSIM: Labor - Wages, Salaries and Other Earnings | Country: Canada | Table: Labour income profile of taxfilers, by sex | Variable: 5-year percent change of median employment income of taxfilers with employment income, Both sexes | Units: $CAD, 2000-2006. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-145.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Earnings; Census; Economic statistics; Wages and salaries; Summary statistics; Socioeconomic status; Official statistics; Personal income; Social 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":[0.002096732,0.002565063,0.002585026,0.008212971,0.003253468,0.004867401,0.005294014,0.001486465,0.09842398],"category_scores_gemma":[0.01721937,0.001803144,0.002061396,0.03922852,0.000609584,0.002488246,0.002241218,0.003048226,0.06342446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05018172,"about_ca_system_score_gemma":0.1221173,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9942396,"about_ca_topic_score_gemma":0.9921356,"domain_scores_codex":[0.9958442,0.0002611226,0.0004162171,0.0005129525,0.001977582,0.0009879364],"domain_scores_gemma":[0.9662971,0.001018092,0.001023551,0.0009853395,0.02914892,0.001526943],"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":[0.00002477992,0.000006129741,0.0008163371,0.0001998594,0.00001602575,0.000005684946,0.00001743603,0.00009578455,0.000008498241,0.0003099601,0.9968876,0.001611845],"study_design_scores_gemma":[0.0001453702,0.00001186195,0.02130814,0.0008239045,0.0000546524,0.0000238434,0.0003818114,0.0004406274,0.0001876772,0.0006501371,0.9758832,0.00008875167],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004608253,0.0000426482,0.00002356115,0.0001096982,0.00002568952,0.00001383543,0.9987755,0.00007005909,0.0008928932],"genre_scores_gemma":[0.0007162618,0.0002499794,0.0004076523,0.0001508076,0.00001655279,0.0001086666,0.9939013,0.0001228829,0.004325925],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09842398,"threshold_uncertainty_score":0.3640956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01848393441984971,"score_gpt":0.2349873589205954,"score_spread":0.2165034245007457,"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."}}