{"id":"W6938871079","doi":"10.6068/dp14ba8e66d3e6","title":"Trend 1997 - 2013. Statistics Canada. CANSIM: Labor - Hours of Work and Work Arrangements | Country: Canada | Table: Labour force survey estimates (LFS), employees by job permanency, North American Industry Classification System (NAICS), sex and age group | Variable: 55 years and over, Finance, insurance, real estate and leasing, Total employees, permanent and temporary, Females | Units: # Persons x 1,000, 1997-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-138.","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; Work (physics); Economic statistics; Recreation; Official statistics; Descriptive statistics; Socioeconomic status; Statistician; Summary statistics; Wages and salaries","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":[0.001873068,0.002286321,0.002815356,0.007018645,0.0028499,0.004312794,0.005118214,0.001346092,0.08443313],"category_scores_gemma":[0.01521363,0.00165881,0.00215213,0.03510157,0.0005147755,0.002028614,0.002167914,0.003146129,0.0494932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04173864,"about_ca_system_score_gemma":0.0990854,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944706,"about_ca_topic_score_gemma":0.9927665,"domain_scores_codex":[0.9964519,0.000241471,0.0004137569,0.0004820828,0.001526154,0.0008846837],"domain_scores_gemma":[0.9711223,0.001051286,0.0009225849,0.0007308953,0.02471678,0.001456128],"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":[0.0000310081,0.000009140783,0.001586802,0.0002871586,0.00002559387,0.000006991258,0.00002925486,0.0001097441,0.000008361179,0.0002607275,0.9957724,0.001872838],"study_design_scores_gemma":[0.0002609058,0.00002259587,0.05242138,0.00132857,0.0001050982,0.00003520596,0.0008521907,0.000636735,0.0001880162,0.0006885131,0.9433517,0.0001089664],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008145082,0.00005062468,0.00002330854,0.0001014039,0.00002636801,0.00001493627,0.9990039,0.00004859362,0.0006493185],"genre_scores_gemma":[0.0009103909,0.0002560783,0.0002866864,0.0001477277,0.0000174412,0.0001292013,0.9945192,0.00007397463,0.003659365],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08443313,"threshold_uncertainty_score":0.3028365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02664253756991113,"score_gpt":0.2496505813786249,"score_spread":0.2230080438087138,"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."}}