{"id":"W6939147854","doi":"10.6068/dp14ba8bb76cd78","title":"Trend 1986 - 2011. Statistics Canada. CANSIM: Income, Pensions, Spending and Wealth - Household, Family and Personal Income | Country: Canada | Table: Earnings of individuals, by selected characteristics and North American Industry Classification System (NAICS) | Variable: Postsecondary certificate or diploma, Wholesale and retail trade, Average earnings | Units: Constant 2011 $CAD $CAD, 1986-2011. 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":"Earnings; Economic statistics; Personal income; Census; Total personal income; Taxable income; Socioeconomic status; Population; Official statistics; 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":[0.001943974,0.002429668,0.002714199,0.008480422,0.003453714,0.004529623,0.005132536,0.001366473,0.07395296],"category_scores_gemma":[0.01638644,0.001608353,0.00202858,0.03956037,0.0006035693,0.00228487,0.00232678,0.00307596,0.04893124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05237624,"about_ca_system_score_gemma":0.1187549,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944739,"about_ca_topic_score_gemma":0.9933599,"domain_scores_codex":[0.9964095,0.0002261764,0.000383642,0.0004955656,0.001628588,0.0008565633],"domain_scores_gemma":[0.9703513,0.0009759878,0.0009370524,0.0008771648,0.02553917,0.001319289],"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":[0.00002444494,0.000006219164,0.001223208,0.0002321104,0.00002172412,0.000006875681,0.00002330372,0.0001067041,0.000008519361,0.0003823074,0.9963655,0.001599136],"study_design_scores_gemma":[0.0001566445,0.00001275157,0.03309648,0.0009271809,0.00007599421,0.00003168327,0.0005046789,0.0004933876,0.0001964541,0.0006497034,0.9637614,0.00009352878],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005893886,0.00004750209,0.00001874509,0.00009158068,0.00001924897,0.00001097953,0.9990754,0.00004482259,0.0006328076],"genre_scores_gemma":[0.0007417759,0.0002354965,0.000269823,0.00009631392,0.00001377244,0.00008610846,0.9953403,0.00006570846,0.003150709],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07395296,"threshold_uncertainty_score":0.380018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04532384612753768,"score_gpt":0.2400603388537445,"score_spread":0.1947364927262069,"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."}}