{"id":"W6976662395","doi":"10.6068/dp14ba8d8e1b787","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: 15 years and over, Health care and social assistance, Females, Total employees, Median 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; Wages and salaries; Wage; Summary statistics; Socioeconomic status; Official statistics; Immigration; Survey data collection","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":[0.002160031,0.00247501,0.003031607,0.007742641,0.002958291,0.004594267,0.005503514,0.001511411,0.09067921],"category_scores_gemma":[0.01688333,0.001878307,0.002209626,0.03902478,0.0005668844,0.002255386,0.002224478,0.003404269,0.05612911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04863148,"about_ca_system_score_gemma":0.1216695,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9943256,"about_ca_topic_score_gemma":0.9925306,"domain_scores_codex":[0.9957429,0.0002802223,0.0004703607,0.0005122175,0.001980554,0.001013782],"domain_scores_gemma":[0.9661279,0.001171667,0.001096551,0.0008516681,0.02915755,0.001594677],"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":[0.00002962149,0.000008565848,0.001046304,0.0002429983,0.00002268106,0.000005831216,0.00001822457,0.0001012009,0.000007640758,0.0002615837,0.9966289,0.001626301],"study_design_scores_gemma":[0.0002806211,0.0000202582,0.03805491,0.001213241,0.00009324685,0.00003104044,0.000565809,0.0006134391,0.0002023734,0.0007572548,0.9580573,0.0001106037],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006257939,0.00004996844,0.00002194454,0.0001160101,0.00003005898,0.00001691703,0.998836,0.00005510653,0.000811502],"genre_scores_gemma":[0.0008032686,0.0002643483,0.0003214758,0.0001750209,0.00001999389,0.0001287698,0.9939134,0.00009654067,0.004277249],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09067921,"threshold_uncertainty_score":0.3528477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03408779698419423,"score_gpt":0.2751577296322223,"score_spread":0.2410699326480281,"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."}}