{"id":"W6901425841","doi":"10.6068/dp14ba8803f1387","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, 20 to 99 employees, Finance, insurance, real estate and leasing, 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; Real estate; 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":[],"consensus_categories":[],"category_scores_codex":[0.002375224,0.00234156,0.002799544,0.008088384,0.00323654,0.004603785,0.005133943,0.001405579,0.1050678],"category_scores_gemma":[0.01809391,0.001826249,0.002061739,0.04020806,0.0005612136,0.002415996,0.002375249,0.002937773,0.06505582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04757039,"about_ca_system_score_gemma":0.1267069,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9942122,"about_ca_topic_score_gemma":0.9917831,"domain_scores_codex":[0.9957536,0.0003020262,0.0004754222,0.0005519419,0.001896193,0.001020796],"domain_scores_gemma":[0.9640058,0.001280214,0.0009648918,0.001071775,0.03094447,0.001732944],"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":[0.00002450716,0.000006424434,0.0008950375,0.0002240842,0.00001877501,0.000005736615,0.00002162374,0.00008439353,0.000008869728,0.0002967764,0.9964838,0.001929883],"study_design_scores_gemma":[0.00017071,0.00001407548,0.02517376,0.000912369,0.00007346411,0.00002617264,0.0005071746,0.0004336211,0.0001676435,0.000667465,0.9717678,0.00008564573],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005383292,0.00004872289,0.00002986118,0.0001163346,0.00003075656,0.00001657942,0.9987351,0.00006960189,0.0008992203],"genre_scores_gemma":[0.0007246691,0.0002766291,0.0004397164,0.0001761734,0.00001871464,0.0001408252,0.9930236,0.0001338171,0.005065784],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1050678,"threshold_uncertainty_score":0.3514867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02964300935594296,"score_gpt":0.2553801028742944,"score_spread":0.2257370935183514,"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."}}