{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002155444,0.002477188,0.003012717,0.007893589,0.003019913,0.00465036,0.005520493,0.001504106,0.09473626],"category_scores_gemma":[0.01672806,0.001887488,0.002146412,0.03973044,0.0005713329,0.002335239,0.002219469,0.003392931,0.06031096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04849651,"about_ca_system_score_gemma":0.1215155,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9943199,"about_ca_topic_score_gemma":0.9924739,"domain_scores_codex":[0.99571,0.0002791195,0.0004632488,0.0005167345,0.002009831,0.001021112],"domain_scores_gemma":[0.9654969,0.001166162,0.001071078,0.0008665558,0.02980648,0.001592853],"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":[0.0000279112,0.000008128713,0.0009672761,0.0002289005,0.00002094975,0.000005630628,0.00001801052,0.00009368471,0.00000753528,0.0002557867,0.9967363,0.001629679],"study_design_scores_gemma":[0.0002611094,0.00001873389,0.03542222,0.001112136,0.00008709587,0.00002962268,0.0005553347,0.0005594864,0.0001948524,0.0007374966,0.9609162,0.0001056991],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006116463,0.00005037863,0.00002272486,0.0001180624,0.00003106177,0.00001689762,0.9987745,0.00005851976,0.0008667333],"genre_scores_gemma":[0.0007758013,0.0002643573,0.0003241662,0.0001749875,0.00002016124,0.0001264734,0.9936818,0.0001031402,0.004529149],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09473626,"threshold_uncertainty_score":0.3518685,"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."}}