{"id":"W6901614854","doi":"10.6068/dp14ba8efd1aa14","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: 25 to 44 years, Other personal (including maternity leave), Professional, scientific and technical 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; Economic statistics; Official statistics; Socioeconomic status; Work (physics); Summary statistics; Turnover; Population statistics; Social statistics","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":[0.002420289,0.002521269,0.00301869,0.008629496,0.00312937,0.004391563,0.005588139,0.001506868,0.08046388],"category_scores_gemma":[0.01962279,0.001814869,0.00255079,0.03965405,0.0005872171,0.00219014,0.002324647,0.003407295,0.04572099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05094779,"about_ca_system_score_gemma":0.1292061,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9957708,"about_ca_topic_score_gemma":0.9945325,"domain_scores_codex":[0.9956871,0.0003156161,0.0005206256,0.0005145758,0.001921682,0.001040468],"domain_scores_gemma":[0.9661176,0.001261193,0.001166726,0.0008915603,0.02897548,0.00158746],"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":[0.00003246335,0.000009616588,0.001611806,0.0003187755,0.0000319832,0.000007034445,0.00002934831,0.0001348928,0.000008821783,0.0002975542,0.9956741,0.001843682],"study_design_scores_gemma":[0.0003130173,0.00002505881,0.05456661,0.001511937,0.0001363354,0.00003851635,0.0007728878,0.0007750966,0.0002193339,0.0008183533,0.9406924,0.0001304308],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007223683,0.00005645573,0.000025581,0.0001090241,0.00002714651,0.00001685798,0.9990718,0.0000522047,0.0005685857],"genre_scores_gemma":[0.0009773853,0.0002937265,0.0003622519,0.0001665208,0.00002176024,0.0001528131,0.9942951,0.00009445044,0.003636093],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08046388,"threshold_uncertainty_score":0.3696538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03583167997363243,"score_gpt":0.2737345120982408,"score_spread":0.2379028321246084,"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."}}