{"id":"W6958118184","doi":"10.6068/dp14ba8efeb0419","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, Total, days lost (including maternity leave), Business, building and other support 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; Summary statistics; Turnover; Work (physics); 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":[0.002489002,0.002478659,0.003052333,0.008568476,0.003120582,0.004335401,0.005603268,0.001500056,0.08457015],"category_scores_gemma":[0.01916662,0.001868365,0.002573616,0.03946625,0.000573892,0.002263015,0.00229142,0.003406214,0.0470786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05248972,"about_ca_system_score_gemma":0.1269484,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958197,"about_ca_topic_score_gemma":0.9944522,"domain_scores_codex":[0.9956648,0.0003158861,0.0005311845,0.0004956158,0.001922688,0.001069844],"domain_scores_gemma":[0.9652137,0.00121664,0.001141277,0.0008750609,0.02994478,0.001608596],"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":[0.00003311955,0.000009774745,0.001532438,0.0003348036,0.00003056836,0.00000725968,0.00002965515,0.0001280467,0.000008724968,0.0003006041,0.9956312,0.001953807],"study_design_scores_gemma":[0.0002936037,0.00002553781,0.05520309,0.001534717,0.0001323509,0.00003986176,0.0007707163,0.0006975077,0.0002194645,0.0007767593,0.9401788,0.0001275178],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007405536,0.00006192959,0.00002610238,0.000113762,0.00002980075,0.00001825046,0.9989723,0.00005416823,0.0006497668],"genre_scores_gemma":[0.001040617,0.0003280801,0.0003813291,0.0001790946,0.00002300647,0.0001586168,0.9936368,0.0001025424,0.004149912],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08457015,"threshold_uncertainty_score":0.3808414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03173654853861907,"score_gpt":0.2609076609137263,"score_spread":0.2291711123751072,"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."}}