{"id":"W6938881276","doi":"10.6068/dp14ba88bdc5216","title":"Trend 1989 - 2011. Statistics Canada. CANSIM: Labor - Wages, Salaries and Other Earnings | Country: Canada | Table: Earnings of individuals, by selected characteristics and North American Industry Classification System (NAICS) | Variable: Graduated high school, Wholesale and retail trade, Average earnings | Units: Constant 2011 $CAD $CAD, 1989-2011. 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; Socioeconomic status; Official statistics; Summary statistics; Immigration; Publication","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":[0.00179357,0.002327699,0.00258403,0.008366548,0.003198943,0.004500086,0.005149602,0.001408314,0.08014488],"category_scores_gemma":[0.01459865,0.001592762,0.001833133,0.03922096,0.0005629947,0.002193632,0.002102163,0.002939655,0.05225912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04793608,"about_ca_system_score_gemma":0.1152486,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944744,"about_ca_topic_score_gemma":0.9930528,"domain_scores_codex":[0.9961451,0.0002283173,0.0003750516,0.0004927714,0.001800012,0.000958778],"domain_scores_gemma":[0.9703354,0.000939346,0.0009857572,0.0007880013,0.02559537,0.001355979],"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":[0.00002362868,0.000007361231,0.001147341,0.0001927126,0.00001911462,0.000006472578,0.00001946977,0.0001046986,0.000007879798,0.0003523876,0.9965795,0.001539471],"study_design_scores_gemma":[0.0001703102,0.00001395709,0.03253795,0.0007965624,0.0000669384,0.00002773664,0.000488251,0.0005409796,0.0002068959,0.000627258,0.9644319,0.00009137711],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006455137,0.00004732996,0.00002046156,0.0001052597,0.00002135032,0.00001220456,0.9989041,0.00005136991,0.0007733742],"genre_scores_gemma":[0.0008442558,0.0002507087,0.0002932452,0.0001199664,0.00001622063,0.00008461609,0.9943891,0.00008246698,0.003919487],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08014488,"threshold_uncertainty_score":0.3478022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02093570598063969,"score_gpt":0.2195218231266346,"score_spread":0.1985861171459949,"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."}}