{"id":"W6958053899","doi":"10.6068/dp14ba8ce5a5274","title":"Trend 1997 - 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: 55 years and over, Total, days lost (excluding maternity leave), Manufacturing, Females | Units: # Days, 1997-2013. 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; Summary statistics; Socioeconomic status; Work (physics); Turnover; Population statistics; Social 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":[0.002310258,0.002584222,0.003071429,0.007781382,0.003215563,0.004570885,0.005805242,0.001559826,0.09167074],"category_scores_gemma":[0.0187705,0.001846807,0.00260098,0.03713753,0.0005818695,0.00229861,0.002388689,0.003393537,0.05318208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04814045,"about_ca_system_score_gemma":0.1196846,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9954326,"about_ca_topic_score_gemma":0.9939773,"domain_scores_codex":[0.9958463,0.0003012031,0.000490362,0.0005198956,0.001834859,0.001007356],"domain_scores_gemma":[0.9672124,0.001239657,0.001062082,0.0009135547,0.02798109,0.001591286],"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":[0.00003169507,0.000008684913,0.001291458,0.0003010399,0.00002874969,0.000006578777,0.00002484811,0.0001193073,0.000008130666,0.0002715001,0.9961622,0.001746001],"study_design_scores_gemma":[0.0003081534,0.00002282633,0.04275087,0.001409345,0.0001252479,0.00003640422,0.0006618642,0.0006778183,0.0002035304,0.0007901622,0.9528896,0.0001241795],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006027284,0.00005306216,0.00002396811,0.0001045365,0.00002749719,0.00001604797,0.9990165,0.00005553966,0.0006426168],"genre_scores_gemma":[0.0008486907,0.0002720096,0.0003387113,0.0001692723,0.00002032031,0.0001402675,0.9944943,0.0001004748,0.003615935],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09167074,"threshold_uncertainty_score":0.3492851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03068433807591087,"score_gpt":0.2551926183499876,"score_spread":0.2245082802740767,"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."}}