{"id":"W6938683684","doi":"10.6068/dp14ba8cf94a33","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 to 24 years, Services-producing sector, Both sexes, Total employees, Average weekly 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; Wages and salaries; Economic statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.001706107,0.001389217,0.002295154,0.0002801541,0.0002016779,0.0004983312,0.001966476,0.0005956843,0.0003152686],"category_scores_gemma":[0.0002375979,0.001394398,5.615329e-7,0.001633276,0.000604941,0.0004534092,0.001084545,0.001635845,0.00001707093],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004376578,"about_ca_system_score_gemma":0.005822767,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9996501,"about_ca_topic_score_gemma":0.9992041,"domain_scores_codex":[0.9919196,0.001454248,0.001626737,0.002177121,0.001581405,0.001240856],"domain_scores_gemma":[0.9920037,0.001177381,0.002384225,0.00325811,0.0002215468,0.0009550565],"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":[0.0003333651,0.0001332556,0.01451449,0.003499698,0.0006803303,0.0001529171,0.00003851097,0.00009274524,0.00003037775,0.00006127016,0.9803773,0.00008575337],"study_design_scores_gemma":[0.000817665,0.0002668068,0.003645284,0.0004548218,0.0005600926,0.0000472508,0.0005701259,0.0006258109,2.561789e-7,4.767808e-8,0.9916304,0.001381459],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001224084,0.005723212,0.000006337293,0.00000206816,0.0006126401,0.001204958,0.9910008,0.0001780673,0.00004778658],"genre_scores_gemma":[0.002002684,0.0007750178,0.0003235367,0.00007971685,0.0001749459,0.00003187522,0.9943295,0.0007735267,0.001509232],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01125309,"threshold_uncertainty_score":0.9998859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02963223849317242,"score_gpt":0.2534007029108173,"score_spread":0.2237684644176449,"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."}}