{"id":"W6920366449","doi":"10.6068/dp14baa322c188","title":"Trend 1999 - 2011. Statistics Canada. CANSIM: Government - Employment and Remuneration | Country: Canada | Province: Nunavut | Table: Labour statistics by business sector industry and non-commercial activity, consistent with the System of National Accounts, by North American Industry Classification System (NAICS) | Variable: Annual average number of hours worked for all jobs, Accommodation and food services, Business sector | Units: , 1999-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-104.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Official statistics; Census; Government (linguistics); Social statistics; Remuneration; Public sector; Summary statistics; Statistics education; Private sector","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":[0.002217263,0.002430003,0.002848845,0.008585733,0.003444189,0.004878379,0.005208572,0.00149502,0.08040421],"category_scores_gemma":[0.01856061,0.001791248,0.002068602,0.041492,0.0006214766,0.002544459,0.002270539,0.003132191,0.04982455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05499331,"about_ca_system_score_gemma":0.1364907,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9948087,"about_ca_topic_score_gemma":0.9933862,"domain_scores_codex":[0.9954752,0.0003109811,0.0004974063,0.0005815768,0.00211137,0.001023371],"domain_scores_gemma":[0.9617777,0.001217122,0.001091051,0.001030135,0.03327321,0.001610856],"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":[0.00002627468,0.000007057997,0.00104671,0.0002374131,0.00002222131,0.000007194753,0.00002113109,0.0001036762,0.000009018737,0.0003345701,0.9966125,0.001572305],"study_design_scores_gemma":[0.0001670754,0.00001416718,0.0290835,0.0009099775,0.0000789336,0.00003021828,0.0005372232,0.0005126733,0.000193081,0.0006477171,0.9677303,0.0000951737],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005766307,0.00005082957,0.00002191456,0.0001208001,0.0000304815,0.00001503525,0.9988689,0.000050338,0.0007840864],"genre_scores_gemma":[0.0008196441,0.000279887,0.0003517354,0.00015479,0.00001964298,0.00011724,0.9941076,0.00009776858,0.004051773],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08040421,"threshold_uncertainty_score":0.3990063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02008127628876206,"score_gpt":0.2350194699087592,"score_spread":0.2149381936199972,"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."}}