{"id":"W6976561643","doi":"10.6068/dp14ba8e5e67350","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 to 24 years, Other personal (including maternity leave), Health care and social assistance, Both sexes | 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; Turnover; Work (physics); Social statistics; Population 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":[0.002437048,0.002561891,0.003043662,0.008520861,0.003081859,0.004366526,0.005664465,0.001501997,0.07895525],"category_scores_gemma":[0.01919996,0.001835565,0.002610223,0.03943922,0.0005854805,0.002178268,0.002328056,0.003438622,0.04431874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05186446,"about_ca_system_score_gemma":0.1302851,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9959128,"about_ca_topic_score_gemma":0.9946538,"domain_scores_codex":[0.9957151,0.0003193659,0.0005232021,0.0005099883,0.001894937,0.001037397],"domain_scores_gemma":[0.9671725,0.00120901,0.00114898,0.0008657304,0.02803299,0.001570962],"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":[0.00003336578,0.00000983075,0.001644095,0.0003334588,0.00003399415,0.000007143251,0.0000295738,0.0001402527,0.000008879505,0.0003101237,0.9955522,0.001897119],"study_design_scores_gemma":[0.0003181896,0.00002545353,0.05492637,0.001570028,0.0001406087,0.00003915047,0.0007645885,0.0008063985,0.0002204264,0.0008256721,0.9402314,0.0001317319],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007213713,0.0000585938,0.00002555105,0.0001101318,0.00002729741,0.00001735313,0.999063,0.00005169509,0.0005743427],"genre_scores_gemma":[0.000997985,0.0003061732,0.0003712573,0.0001710679,0.00002191936,0.0001573865,0.9942542,0.00009413461,0.003625887],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07895525,"threshold_uncertainty_score":0.3763047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03093515831885818,"score_gpt":0.2677467446616373,"score_spread":0.2368115863427792,"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."}}