{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001164316,0.001117286,0.001589612,0.00009234783,0.0005145865,0.0006332603,0.00359925,0.0004984408,0.0001922512],"category_scores_gemma":[0.0002734251,0.0009160882,1.922826e-7,0.0004181461,0.001888996,0.00085894,0.001587882,0.001386881,0.00001006227],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006150932,"about_ca_system_score_gemma":0.03733318,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9997074,"about_ca_topic_score_gemma":0.9996504,"domain_scores_codex":[0.9926566,0.0008731469,0.001322448,0.001957373,0.002294439,0.0008960261],"domain_scores_gemma":[0.9878041,0.001590041,0.004259189,0.00476084,0.001015897,0.0005699162],"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":[0.0002370679,0.00006346065,0.01814013,0.007277905,0.0007613442,0.0001047263,0.00000744304,0.000008849524,0.000006127083,0.002892096,0.9704231,0.00007777286],"study_design_scores_gemma":[0.0008969167,0.00008026524,0.001212084,0.000422139,0.0008907945,0.0004273726,0.00145378,0.00287167,5.988628e-8,4.012839e-8,0.9907635,0.0009813054],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003928807,0.002297036,0.00001987829,0.000009087921,0.0002422423,0.001776607,0.9949212,0.00006298836,0.0006316529],"genre_scores_gemma":[0.0006409056,0.0009174666,0.0004556054,0.0001917827,0.0001187471,0.00005535417,0.9956477,0.0004403954,0.001532059],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03671809,"threshold_uncertainty_score":0.999329,"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."}}