{"id":"W6920557079","doi":"10.6068/dp14ba8ccbb084","title":"Trend 1987 - 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: 15 years and over, Own illness or disability, Accommodation and food services, Females | Units: # Days, 1987-2013. 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; Summary statistics; Work (physics); Socioeconomic status; Turnover; Social statistics; Population statistics; General Social Survey","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":[0.002502238,0.002509437,0.003087626,0.008850308,0.003083041,0.004516157,0.005818089,0.001515552,0.08257495],"category_scores_gemma":[0.01896615,0.001894049,0.002591573,0.0411272,0.0006022798,0.002351845,0.002345873,0.003376919,0.04893036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05491941,"about_ca_system_score_gemma":0.1412963,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9961503,"about_ca_topic_score_gemma":0.9947175,"domain_scores_codex":[0.9952048,0.0003301001,0.0005433029,0.0005296583,0.002226166,0.001166032],"domain_scores_gemma":[0.9631667,0.001256809,0.001207766,0.0008949119,0.03175764,0.001716188],"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":[0.00003024243,0.000009264263,0.001374942,0.0002984622,0.00002782296,0.000006632302,0.00002667272,0.0001228527,0.000007798933,0.0002960509,0.9960356,0.001763495],"study_design_scores_gemma":[0.0002793524,0.00002416928,0.04830562,0.001379117,0.000121227,0.00003623204,0.0007501696,0.0007088713,0.000215875,0.00072296,0.9473339,0.0001223194],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007257064,0.00005872272,0.00002573899,0.0001232872,0.00002959208,0.00001761448,0.9989091,0.00005863882,0.0007046803],"genre_scores_gemma":[0.001045928,0.0003269744,0.0003913103,0.000186327,0.00002322045,0.0001555225,0.9931245,0.0001112361,0.004634957],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08257495,"threshold_uncertainty_score":0.39847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02673424818158323,"score_gpt":0.2554354960266106,"score_spread":0.2287012478450274,"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."}}