{"id":"W6957787743","doi":"10.6068/dp14ba8ce593a73","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: 25 to 54 years, Other personal (excluding maternity leave), Educational services, Males | 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":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Official statistics; Economic statistics; Socioeconomic status; Summary statistics; 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":[0.002457779,0.002621168,0.003026753,0.008548193,0.00313428,0.004669633,0.005687169,0.001528249,0.09469033],"category_scores_gemma":[0.01900746,0.001861702,0.002632824,0.03877485,0.0005808098,0.00241359,0.002484156,0.00336096,0.05647067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04669242,"about_ca_system_score_gemma":0.119586,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9952368,"about_ca_topic_score_gemma":0.9935949,"domain_scores_codex":[0.9955919,0.0003187532,0.0005043549,0.0005360442,0.001977149,0.001071715],"domain_scores_gemma":[0.9667854,0.00127958,0.001103956,0.0009670854,0.02822749,0.001636538],"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":[0.00003064505,0.000008624022,0.001243033,0.0002839348,0.00002798647,0.000006380739,0.00002496476,0.0001160729,0.000007812701,0.0002705555,0.9962062,0.001773901],"study_design_scores_gemma":[0.0002791362,0.00002158787,0.0404873,0.001217314,0.0001139683,0.00003361371,0.0005958883,0.0006508356,0.0001870884,0.0007027054,0.955597,0.0001135014],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006033802,0.00005065431,0.00002489015,0.00009947128,0.00002667513,0.00001582098,0.9989873,0.00005997207,0.0006749565],"genre_scores_gemma":[0.0007967703,0.0002536765,0.0003177987,0.0001485719,0.00001946261,0.0001281842,0.9945123,0.0001036775,0.00371941],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09469033,"threshold_uncertainty_score":0.3387788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02657104812034205,"score_gpt":0.2572507835956335,"score_spread":0.2306797354752915,"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."}}