{"id":"W6976382396","doi":"10.6068/dp14ba8dcb70e94","title":"Trend 1997 - 2013. Statistics Canada. CANSIM: Labor - Labor Mobility, Turnover and Work Absences | Country: Canada | Table: Labour force survey estimates (LFS), average days lost for personal reasons per full-time employee by North American Industry Classification System (NAICS), sex and age group | Variable: 55 to 64 years, Other personal (excluding maternity leave), Services-producing sector, Both sexes | Units: # Days, 1997-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-141.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Education Methods and Technologies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Official statistics; Economic statistics; Summary statistics; Socioeconomic status; Work (physics); Turnover; Population 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":[0.002409203,0.002521247,0.00295272,0.008093439,0.003096426,0.004488238,0.005603634,0.001476875,0.08660185],"category_scores_gemma":[0.01866361,0.001842433,0.00256308,0.03765345,0.0005724994,0.002238182,0.002339031,0.003404151,0.0488035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04866603,"about_ca_system_score_gemma":0.1220959,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9955667,"about_ca_topic_score_gemma":0.9941934,"domain_scores_codex":[0.9958043,0.0003038945,0.0004999762,0.0005137337,0.001863837,0.001014252],"domain_scores_gemma":[0.9668307,0.001236875,0.001097681,0.0009084928,0.02833692,0.001589331],"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":[0.00003289458,0.000008931725,0.00142168,0.0003072009,0.00003026928,0.0000068513,0.0000265335,0.000120219,0.000008688925,0.0002803604,0.9958917,0.001864763],"study_design_scores_gemma":[0.0003103481,0.00002405401,0.04887554,0.00144143,0.0001273811,0.00003732073,0.0007079518,0.0007034158,0.000214725,0.0007817715,0.9466494,0.00012666],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006665083,0.00005411512,0.00002470681,0.0001088688,0.00002818513,0.00001692078,0.9990156,0.00005437704,0.0006306789],"genre_scores_gemma":[0.0009121278,0.0002834274,0.0003503553,0.0001703466,0.00002085069,0.0001456715,0.994221,0.00009923962,0.003797049],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08660185,"threshold_uncertainty_score":0.3530984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03983474111114589,"score_gpt":0.2899304975878357,"score_spread":0.2500957564766898,"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."}}