{"id":"W6976869721","doi":"10.6068/dp14ba842d50999","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: 45 years and over, More than 500 employees, Educational services, Males | 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":"Organizational Management and Change","field":"Business, Management and Accounting","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003729418,0.0007425758,0.0007773377,0.0001651304,0.0002897239,0.001223465,0.00132322,0.0003728836,0.0007627436],"category_scores_gemma":[0.00009172571,0.0007622022,2.526502e-7,0.0009930066,0.0002905911,0.000884905,0.0008767268,0.0006283082,0.00000869427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002209454,"about_ca_system_score_gemma":0.002330236,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9994504,"about_ca_topic_score_gemma":0.9991399,"domain_scores_codex":[0.9963718,0.0001304308,0.0006407325,0.001113742,0.001088494,0.0006547853],"domain_scores_gemma":[0.9969973,0.0004841012,0.000968118,0.00119606,0.0001312994,0.0002231531],"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":[0.00002853412,0.00008766166,0.03773244,0.001672384,0.0002820352,0.00005556889,0.00000414512,0.000004414498,3.015908e-7,0.0007613057,0.9593309,0.0000403343],"study_design_scores_gemma":[0.000477714,0.00002755676,0.01340692,0.00009529194,0.0004171317,0.000009990609,0.00148408,0.0006703532,3.751886e-9,2.997826e-7,0.982587,0.0008236094],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002830902,0.00115447,0.000001869203,0.00002998994,0.0004518116,0.00061551,0.9970656,0.0001080159,0.0002896284],"genre_scores_gemma":[0.0008750443,0.0005356437,0.00007798465,0.000562637,0.0005885414,0.0000362883,0.9928995,0.0002427303,0.004181651],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02432552,"threshold_uncertainty_score":0.9998134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02041420839975999,"score_gpt":0.2276477459740678,"score_spread":0.2072335375743078,"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."}}