{"id":"W6957749107","doi":"10.6068/dp14ba8d4293393","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 years and over, Other personal (including maternity leave), Total, all industries, Males | 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; 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":[0.002403362,0.002496252,0.003027051,0.008317965,0.003100027,0.004372165,0.00574179,0.001506561,0.0781372],"category_scores_gemma":[0.01851038,0.00183157,0.002537101,0.03836359,0.0005894003,0.00218686,0.002266606,0.00344102,0.04539139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05068089,"about_ca_system_score_gemma":0.1250843,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9956773,"about_ca_topic_score_gemma":0.9944187,"domain_scores_codex":[0.9957969,0.0003083439,0.0004973673,0.0005099891,0.001868411,0.001018961],"domain_scores_gemma":[0.9669694,0.001210543,0.001127205,0.0008707605,0.02824033,0.001581653],"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":[0.0000313212,0.000009391326,0.00147883,0.0002996202,0.00003035923,0.000006841136,0.00002643483,0.0001270069,0.000008391246,0.0002782225,0.9959651,0.001738367],"study_design_scores_gemma":[0.0003195558,0.00002514265,0.05331117,0.001422926,0.0001354635,0.00003949599,0.0007180702,0.0007852978,0.0002203451,0.0007928972,0.9421023,0.0001272344],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007042979,0.00005551216,0.00002492619,0.0001070585,0.00002723778,0.00001669819,0.9990857,0.00005270764,0.0005597189],"genre_scores_gemma":[0.0009374527,0.0002762888,0.0003491342,0.0001638875,0.0000215479,0.0001443543,0.9945497,0.00009256298,0.003465076],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0781372,"threshold_uncertainty_score":0.3677173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0369578719183635,"score_gpt":0.2590557058670512,"score_spread":0.2220978339486877,"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."}}