{"id":"W6976624623","doi":"10.6068/dp14ba8a9fc6a2","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, Other services, Females, Part-time, 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","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":[0.00209715,0.002520716,0.002986896,0.00779993,0.002887694,0.004672258,0.00543208,0.001526719,0.09004551],"category_scores_gemma":[0.01680223,0.001852729,0.002108773,0.04004919,0.000580468,0.002266659,0.002188112,0.003347538,0.05861774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04576695,"about_ca_system_score_gemma":0.1127692,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9936467,"about_ca_topic_score_gemma":0.9918209,"domain_scores_codex":[0.9958604,0.0002724428,0.0004475142,0.0005246271,0.001894069,0.001000908],"domain_scores_gemma":[0.9671245,0.001193596,0.001090101,0.0008910799,0.02813264,0.001568027],"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":[0.00002785901,0.000007835733,0.0009666478,0.0002255273,0.0000207092,0.000005446823,0.0000170572,0.00009633121,0.000007425517,0.000239487,0.9969061,0.001479573],"study_design_scores_gemma":[0.0002700546,0.00001773055,0.03271571,0.001082448,0.00008365583,0.00002859701,0.0005071617,0.0005560961,0.0001946673,0.0007020755,0.9637411,0.0001008409],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005372959,0.00004412566,0.00001933017,0.000101256,0.00002659746,0.00001420242,0.9989917,0.00005187565,0.0006972611],"genre_scores_gemma":[0.0006990195,0.0002257022,0.0002746218,0.0001489388,0.00001812604,0.0001113756,0.9948696,0.00009058829,0.003561968],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09004551,"threshold_uncertainty_score":0.332064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03222833409889297,"score_gpt":0.2588424820041426,"score_spread":0.2266141479052496,"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."}}