{"id":"W2182302514","doi":"10.1016/j.socscimed.2015.10.056","title":"Illness related wage and productivity losses: Valuing ‘presenteeism’","year":2015,"lang":"en","type":"article","venue":"Social Science & Medicine","topic":"Workplace Health and Well-being","field":"Health Professions","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; St. Paul's Hospital; Centre for Advancing Health Outcomes; University of British Columbia","funders":"Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"Presenteeism; Absenteeism; Productivity; Wage; Labour economics; Demographic economics; Proxy (statistics); Marginal product; Economics; Work (physics); Business; Production (economics); Microeconomics; Economic growth; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.008031218,0.0001414672,0.0003239054,0.00014828,0.002963357,0.00001162545,0.0002539811,0.000149454,0.0001000168],"category_scores_gemma":[0.003653903,0.0001055733,0.00001782168,0.001328437,0.001689577,0.000396776,0.0001581838,0.0007290368,0.00005341798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002928075,"about_ca_system_score_gemma":0.001089821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001234791,"about_ca_topic_score_gemma":0.00005921113,"domain_scores_codex":[0.9969148,0.0004414998,0.0004241245,0.0004766647,0.0008417508,0.0009011828],"domain_scores_gemma":[0.9983391,0.0002737903,0.0002077913,0.0002126379,0.0003555914,0.0006111498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001411136,0.00008297143,0.3612174,0.0003249781,0.00001215751,0.00003417995,0.5176066,0.000003042541,0.002184595,0.02953993,0.03496533,0.05388779],"study_design_scores_gemma":[0.01295217,0.0008684041,0.3046036,0.00280644,0.0001835267,0.00004405354,0.3340727,0.001019543,0.0004187165,0.1200624,0.2213733,0.001595123],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.895802,0.0003550515,0.00006013939,0.02838786,0.002524199,0.0006936977,0.000001206159,0.0001220052,0.07205389],"genre_scores_gemma":[0.9953095,0.00003304775,0.00001986705,0.001175316,0.00128676,0.00003271087,0.000003027742,0.00001365163,0.002126084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.186408,"threshold_uncertainty_score":0.9983346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05381952678024443,"score_gpt":0.4308437431498685,"score_spread":0.377024216369624,"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."}}