{"id":"W2026352366","doi":"10.1097/mlr.0000000000000017","title":"How Much do Preexisting Chronic Conditions Contribute to Age Differences in Health Care Expenditures After a Work-related Musculoskeletal Injury?","year":2013,"lang":"en","type":"article","venue":"Medical Care","topic":"Musculoskeletal pain and rehabilitation","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Work & Health; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Work (physics); Health care; Medicine; Musculoskeletal injury; Gerontology; Environmental health; Psychology; Alternative medicine; Economics; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002681741,0.0002796858,0.0006067236,0.0002427739,0.0001286425,0.0000745412,0.0001673725,0.0003250233,0.001761517],"category_scores_gemma":[0.001094212,0.0002060703,0.00021956,0.0003597303,0.0002367099,0.0001146622,0.00009164742,0.0006621905,0.00008269368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005847202,"about_ca_system_score_gemma":0.0003599308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004063015,"about_ca_topic_score_gemma":0.0008078298,"domain_scores_codex":[0.9971352,0.0003153112,0.0005407226,0.000508153,0.0008850773,0.0006155682],"domain_scores_gemma":[0.9983264,0.0002377775,0.0001006579,0.0003490095,0.0001801518,0.0008060622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000534208,0.0009252228,0.4547884,0.02385656,0.0004426902,0.0006561137,0.1297033,0.000008623319,0.001522018,0.001263399,0.02595916,0.3603402],"study_design_scores_gemma":[0.002833132,0.002023671,0.9621462,0.004306853,0.00003656904,0.000006739697,0.02400888,0.00003567541,0.00003496346,0.0001589455,0.003972225,0.0004362133],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9755675,0.00662358,0.00006651536,0.01471365,0.0003624476,0.002046858,0.00005204079,0.0001165082,0.0004509157],"genre_scores_gemma":[0.9969443,0.00003747653,0.0001537991,0.0009030295,0.0003261449,0.0008374727,0.0004773393,0.0000297157,0.0002907026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5073577,"threshold_uncertainty_score":0.999151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007308676105869154,"score_gpt":0.2959195392060865,"score_spread":0.2886108631002173,"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."}}