{"id":"W6957931561","doi":"10.6068/dp15b15bdc7c952","title":"Most Recent Data (2012). Statistics Canada. CANSIM: Labor - Wages, Salaries and Other Earnings | Country: Canada | Province: Alberta | 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: Defence services, Number of employee jobs | Units: , 2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-145.","year":2017,"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; Wages and salaries; Official statistics; Summary statistics; National accounts; Socioeconomic status; Statistics education; National Income and Product Accounts","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":[0.002057879,0.002478151,0.002747947,0.007953066,0.003474898,0.005196751,0.005336175,0.001751318,0.1127412],"category_scores_gemma":[0.02001452,0.001741324,0.00179564,0.04395993,0.0007321429,0.00235772,0.002328074,0.003456366,0.0787376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04611132,"about_ca_system_score_gemma":0.1123768,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9916369,"about_ca_topic_score_gemma":0.9907544,"domain_scores_codex":[0.9955917,0.0002831306,0.0004111331,0.0006087645,0.002093274,0.00101207],"domain_scores_gemma":[0.9624502,0.001779838,0.00107117,0.001284291,0.03159754,0.001817007],"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":[0.00001466885,0.000005368735,0.0005231159,0.0001378247,0.00001045856,0.0000042424,0.00001283777,0.00007699431,0.000006101434,0.0001977512,0.9981545,0.0008562704],"study_design_scores_gemma":[0.0001627309,0.000008496927,0.0167128,0.0006432077,0.00004495431,0.00002003633,0.0003628294,0.0003251406,0.0001373605,0.0006075043,0.9809006,0.00007430447],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003345284,0.00003331356,0.0000130206,0.00008763855,0.00001914095,0.000007382895,0.9991149,0.00004354199,0.0006475868],"genre_scores_gemma":[0.0004414759,0.0001495398,0.0002175312,0.0001023163,0.00001342788,0.00006100753,0.9962233,0.00007459658,0.002716707],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1127412,"threshold_uncertainty_score":0.377157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01768827298565713,"score_gpt":0.2366822844604962,"score_spread":0.2189940114748391,"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."}}