{"id":"W6938967581","doi":"10.6068/dp14ba8bc1b0745","title":"Trend 1997 - 2013. Statistics Canada. CANSIM: Labor - Wages, Salaries and Other Earnings | Country: Canada | Table: Labour force survey estimates (LFS), wages of employees by type of work, North American Industry Classification System (NAICS), sex and age group | Variable: 55 years and over, Public administration, Females, Part-time, Average hourly wage rate | Units: Current $CAD, 1997-2013. 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; Wage; Wages and salaries; Summary statistics; Official statistics; Socioeconomic status; 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":[0.002093955,0.002537984,0.003006801,0.007822992,0.002905244,0.004687797,0.00547831,0.001543722,0.08901799],"category_scores_gemma":[0.01691001,0.001858994,0.002106916,0.04015191,0.000586469,0.002274025,0.002200857,0.003362061,0.05949445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0453144,"about_ca_system_score_gemma":0.1125094,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.99347,"about_ca_topic_score_gemma":0.9916648,"domain_scores_codex":[0.9958562,0.0002753147,0.0004485095,0.0005305929,0.001895292,0.0009940641],"domain_scores_gemma":[0.967072,0.001197784,0.001093433,0.000908308,0.02816795,0.001560566],"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":[0.00002717644,0.000007660841,0.0009389993,0.000221962,0.00002056774,0.000005356909,0.00001664645,0.00009449945,0.000007402051,0.0002352536,0.9969945,0.001429995],"study_design_scores_gemma":[0.0002679466,0.00001732272,0.03157631,0.00105716,0.00008387079,0.00002813816,0.0004907392,0.000546344,0.0001932251,0.0006979105,0.9649411,0.00009998989],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000518083,0.00004321782,0.00001901558,0.00009867614,0.00002604004,0.00001390577,0.9990219,0.00005159869,0.0006738083],"genre_scores_gemma":[0.0006607634,0.0002160557,0.0002660206,0.0001429379,0.00001760132,0.0001077514,0.9951611,0.00008748517,0.003340309],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08901799,"threshold_uncertainty_score":0.3287805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04079241630452133,"score_gpt":0.2662378342270528,"score_spread":0.2254454179225315,"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."}}