{"id":"W6957870150","doi":"10.6068/dp14ba8ab70ed60","title":"Trend 1987 - 2013. Statistics Canada. CANSIM: Labor - Employment and Unemployment | 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, Total, days lost (including maternity leave), Other services, Females | Units: # Days, 1987-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-136.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Unemployment; Census; Official statistics; Economic statistics; Summary statistics; Socioeconomic status; Descriptive statistics; Social statistics; Wages and salaries; 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":[0.002395118,0.002272091,0.003090132,0.008154976,0.003175094,0.00486838,0.005404757,0.001489884,0.08476631],"category_scores_gemma":[0.01875062,0.001966079,0.002377417,0.03909511,0.0006255529,0.002373964,0.00241025,0.003189228,0.05286423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05574393,"about_ca_system_score_gemma":0.1486044,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9959868,"about_ca_topic_score_gemma":0.9945406,"domain_scores_codex":[0.99532,0.0003116778,0.0005246145,0.0005521829,0.00212101,0.001170587],"domain_scores_gemma":[0.9627098,0.001367962,0.001232049,0.0009583599,0.03179025,0.001941381],"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":[0.00003195207,0.000008887597,0.001259686,0.0002641469,0.00002525063,0.000006302725,0.00002456606,0.0001098895,0.00000786626,0.000274453,0.9963455,0.001641528],"study_design_scores_gemma":[0.000271812,0.00002272221,0.04250443,0.001248957,0.0001041746,0.00003464885,0.0006743157,0.000660517,0.0002183119,0.0006197371,0.9535214,0.0001191107],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007454326,0.00005257748,0.00002392735,0.0001232681,0.00002960384,0.00001631497,0.9988328,0.00006620694,0.0007807984],"genre_scores_gemma":[0.001055533,0.0003160063,0.0003824853,0.0002004997,0.00002264172,0.0001447626,0.9927711,0.0001274737,0.004979425],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08476631,"threshold_uncertainty_score":0.4044524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03584589007874376,"score_gpt":0.2630226266335562,"score_spread":0.2271767365548124,"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."}}