{"id":"W6920551951","doi":"10.6068/dp14ba8728c2d97","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: 65 years and over, More than 500 employees, Total employees, all industries, Females | 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; Population statistics; Statistical analysis","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":[0.002313304,0.002416093,0.002889889,0.008537038,0.003461158,0.004815144,0.005304003,0.001460743,0.09890454],"category_scores_gemma":[0.01807888,0.001814138,0.002143105,0.04096182,0.0005854766,0.00239368,0.002375341,0.003020752,0.06403962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04999232,"about_ca_system_score_gemma":0.1302055,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946202,"about_ca_topic_score_gemma":0.9925526,"domain_scores_codex":[0.995752,0.0002979518,0.0004708861,0.0005717557,0.001899958,0.001007477],"domain_scores_gemma":[0.965817,0.001242108,0.0009532687,0.001041832,0.02933168,0.001614153],"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":[0.00002271976,0.000005961109,0.0008789221,0.0002196101,0.00001961418,0.000005848772,0.00002063102,0.00008538712,0.000008252151,0.0003040137,0.9965864,0.001842526],"study_design_scores_gemma":[0.0001631797,0.00001269764,0.02327662,0.0008972049,0.00007563744,0.00002683129,0.0004864233,0.0004369528,0.0001628051,0.0006914112,0.9736821,0.00008819431],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004982001,0.00005180585,0.00002746954,0.0001209227,0.00003033783,0.00001443073,0.9988261,0.00006410177,0.0008149866],"genre_scores_gemma":[0.0007141522,0.00028394,0.000409587,0.0001749891,0.00001855507,0.0001259635,0.9936274,0.0001206481,0.004524811],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09890454,"threshold_uncertainty_score":0.3627213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03442352021044186,"score_gpt":0.2580661124072876,"score_spread":0.2236425921968457,"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."}}