{"id":"W6901703654","doi":"10.6068/dp14ba8976bcc63","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, Trade, Males, 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002087496,0.002521678,0.00296051,0.007770662,0.002959042,0.004558177,0.005479165,0.001482478,0.09235051],"category_scores_gemma":[0.01633132,0.001844605,0.002088452,0.04016186,0.0005729959,0.002308545,0.00214974,0.003302086,0.0606197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04618496,"about_ca_system_score_gemma":0.1156019,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9938127,"about_ca_topic_score_gemma":0.9917924,"domain_scores_codex":[0.9958889,0.0002695498,0.0004401293,0.0005166943,0.001885604,0.0009991225],"domain_scores_gemma":[0.9667317,0.00113337,0.001029173,0.0008617949,0.02870677,0.0015373],"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":[0.00002746298,0.000007750657,0.0009304372,0.0002222215,0.00002024856,0.000005486858,0.00001771686,0.00009198741,0.000007804662,0.0002464212,0.9968889,0.001533589],"study_design_scores_gemma":[0.0002623325,0.0000173839,0.03256243,0.001022597,0.00008367938,0.00002836605,0.0005051055,0.0005294489,0.0002011244,0.0007040683,0.9639839,0.0000996019],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000562236,0.00004426761,0.00002011181,0.0001036921,0.00002656813,0.00001494249,0.9989115,0.00005584473,0.0007668409],"genre_scores_gemma":[0.0006982816,0.0002264754,0.0002879563,0.0001479771,0.00001785289,0.0001136536,0.9946402,0.00009707017,0.003770514],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9076495,"threshold_uncertainty_score":0.3350969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03325519765595156,"score_gpt":0.2570774255593928,"score_spread":0.2238222279034412,"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."}}