{"id":"W6957669104","doi":"10.6068/dp14ba8dcbc8a96","title":"Trend 1986 - 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: Postsecondary certificate or diploma, Accommodation and food services, Number of persons (number x 1,000) | Units: Constant 2011 $CAD, 1986-2011. 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; Socioeconomic status; Official statistics; Summary statistics; Social security; Wages and salaries; Immigration","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":[0.002049816,0.002330688,0.002741602,0.008573342,0.003084616,0.00460664,0.004997846,0.001403473,0.08184071],"category_scores_gemma":[0.01544647,0.001780025,0.001958264,0.03985085,0.0005902885,0.002339178,0.002067984,0.003181615,0.0546006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05328098,"about_ca_system_score_gemma":0.1334706,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9945634,"about_ca_topic_score_gemma":0.9929031,"domain_scores_codex":[0.9954745,0.0002631565,0.0004344961,0.0005366214,0.002226731,0.001064511],"domain_scores_gemma":[0.9653211,0.001045854,0.001148292,0.0008330523,0.03016846,0.001483229],"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":[0.00002632765,0.000008287253,0.001167764,0.0002155677,0.0000192131,0.000006086686,0.00001891485,0.0001130392,0.000007793422,0.0003361846,0.9965075,0.001573384],"study_design_scores_gemma":[0.0001716057,0.00001609761,0.03648783,0.0008443994,0.00006628576,0.00002715753,0.0004694635,0.0005008586,0.0002089321,0.000520166,0.9605979,0.00008927289],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007616162,0.00005774906,0.00002309492,0.0001246697,0.00003139699,0.00001468267,0.9986284,0.00005681726,0.0009870414],"genre_scores_gemma":[0.0009817538,0.0003131011,0.0003144974,0.0001481343,0.00002149343,0.0001023241,0.9919356,0.0000968258,0.006086238],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08184071,"threshold_uncertainty_score":0.3865824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03001508025750101,"score_gpt":0.2451800014110755,"score_spread":0.2151649211535744,"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."}}