{"id":"W6901344220","doi":"10.6068/dp14ba8af51aa74","title":"Trend 2007 - 2012. Statistics Canada. CANSIM: Labor - Wages, Salaries and Other Earnings | Country: Canada | Table: Labour statistics consistent with the System of National Accounts (SNA), by province and territory, job category and North American Industry Classification System (NAICS) | Variable: Automotive equipment rental and leasing, Employee's compensation per hour worked | Units: , 2007-2012. 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; Economic statistics; Census; Summary statistics; Official statistics; Wages and salaries; National accounts; Descriptive statistics; Socioeconomic status; Statistics education","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":[0.001719884,0.002593729,0.002769403,0.008183844,0.002971288,0.00476801,0.00507534,0.001508846,0.07735513],"category_scores_gemma":[0.01513175,0.001711768,0.00186857,0.04061658,0.0006179885,0.002388185,0.002063927,0.003125658,0.05922906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04674564,"about_ca_system_score_gemma":0.1111586,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.99312,"about_ca_topic_score_gemma":0.9914871,"domain_scores_codex":[0.9960968,0.000239869,0.0003613227,0.0005379494,0.001814603,0.0009494415],"domain_scores_gemma":[0.9704322,0.0009770979,0.0009742464,0.0008687716,0.02545615,0.001291455],"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":[0.00002118796,0.000006393931,0.0008747869,0.000152964,0.00001656692,0.000005373862,0.00001395242,0.00009976451,0.000007436645,0.0002504898,0.9974322,0.001118979],"study_design_scores_gemma":[0.0001653235,0.00001183348,0.02449931,0.0006941765,0.00005600051,0.00002493582,0.000413977,0.0005697102,0.0002123784,0.000582204,0.9726834,0.00008683592],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005434562,0.00003923704,0.00001665044,0.00009117598,0.00002190666,0.000009205461,0.9990859,0.000052363,0.0006291617],"genre_scores_gemma":[0.0006189168,0.0001659667,0.0002218577,0.00009769436,0.0000146663,0.0000683835,0.9958665,0.00007583612,0.002870076],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07735513,"threshold_uncertainty_score":0.339165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02149548731734584,"score_gpt":0.2358419712341613,"score_spread":0.2143464839168154,"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."}}