{"id":"W6901406502","doi":"10.6068/dp14baa3ad5af53","title":"Trend 1997 - 2011. Statistics Canada. CANSIM: Government - Employment and Remuneration | Country: Canada | Province: Prince Edward Island | 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: , 1997-2011. 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; Census; Official statistics; Government (linguistics); Remuneration; Social statistics; Public sector; Government sector; Wages and salaries; 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":[0.002160653,0.002292793,0.002742482,0.008450959,0.003312259,0.004625674,0.004844062,0.001422734,0.08325816],"category_scores_gemma":[0.01840206,0.001751789,0.001955826,0.04192125,0.0006076614,0.002514203,0.002275729,0.003134208,0.05319542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05222534,"about_ca_system_score_gemma":0.138543,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.994818,"about_ca_topic_score_gemma":0.9933919,"domain_scores_codex":[0.9956457,0.0002955356,0.000477266,0.0005434618,0.002041843,0.0009961418],"domain_scores_gemma":[0.9613259,0.001254498,0.001074121,0.001034015,0.03370372,0.001607691],"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":[0.00002386944,0.000006525504,0.001023189,0.000229794,0.00002110738,0.000006811807,0.00002232979,0.00009437107,0.000008575733,0.0003261357,0.9966586,0.00157872],"study_design_scores_gemma":[0.0001497409,0.00001338168,0.02825221,0.0008806589,0.00007369364,0.00002806873,0.0005781983,0.0004543869,0.0001811128,0.0006154995,0.9686839,0.00008924733],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006377769,0.00004998927,0.00002392044,0.0001283907,0.00003035095,0.00001548545,0.998751,0.00005415189,0.0008828689],"genre_scores_gemma":[0.0008461905,0.0002873009,0.0003630556,0.0001653044,0.00001958242,0.000120182,0.9934897,0.0001073909,0.004601353],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08325816,"threshold_uncertainty_score":0.3789231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01813677317129453,"score_gpt":0.2342156766978307,"score_spread":0.2160789035265362,"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."}}