{"id":"W6976310133","doi":"10.6068/dp14ba8728b9196","title":"Trend 1997 - 2013. Statistics Canada. CANSIM: Labor - Industries | Country: Canada | Table: Labour force survey estimates (LFS), employees by establishment size, North American Industry Classification System (NAICS), sex and age group | Variable: 25 to 54 years, Total employees, all establishment sizes, Other services, Both sexes | Units: # Persons x 1,000, 1997-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-139.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Economic statistics; Official statistics; Summary statistics; Wages and salaries; Socioeconomic status; Statistical analysis; Population statistics","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":[0.002362486,0.002421339,0.002886428,0.008786411,0.003434875,0.004813287,0.005277327,0.001439797,0.1034498],"category_scores_gemma":[0.01837632,0.001839701,0.002151862,0.04171872,0.0005806407,0.002401327,0.00238713,0.003012276,0.06485754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05117055,"about_ca_system_score_gemma":0.1337011,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9947363,"about_ca_topic_score_gemma":0.992565,"domain_scores_codex":[0.9955949,0.0003049534,0.0004919599,0.0005832557,0.001990628,0.001034316],"domain_scores_gemma":[0.9648051,0.001276667,0.000976263,0.001054326,0.03023626,0.00165137],"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":[0.00002248003,0.000005993379,0.0008755832,0.0002256449,0.00001960812,0.000005790448,0.00002118801,0.00008703528,0.000008319903,0.0003120809,0.9964952,0.001921096],"study_design_scores_gemma":[0.0001588066,0.00001274774,0.02360219,0.0009007835,0.00007492071,0.00002629558,0.0004895462,0.0004328366,0.0001606778,0.0006852155,0.9733688,0.00008713362],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005124605,0.00005352705,0.00002943588,0.0001240821,0.00003174241,0.00001549909,0.9987362,0.00006731805,0.0008910492],"genre_scores_gemma":[0.0007573536,0.0003078725,0.0004433204,0.0001834999,0.00001934446,0.0001371036,0.9929866,0.0001315522,0.005033345],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8965502,"threshold_uncertainty_score":0.37127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02333695004595835,"score_gpt":0.2476241542233736,"score_spread":0.2242872041774153,"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."}}