Occupational Exposure and Risk of Central Nervous System Demyelination
Bibliographic record
Abstract
Inconsistent evidence exists regarding the association between work-related factors and risk of multiple sclerosis (MS). We examined the association between occupational exposures and risk of a first clinical diagnosis of central nervous system demyelination (FCD), which is strongly associated with progression to MS, in a matched case-control study of 276 FCD cases and 538 controls conducted in Australia (2003-2006). Using a personal residence and work calendar, information on occupational history and exposure to chemicals and animals was collected through face-to-face interviews. Few case-control differences were noted. Fewer cases had worked as professionals (≥6 years) than controls (adjusted odds ratio (AOR) = 0.60, 95% confidence interval (CI): 0.37, 0.96). After further adjustment for number of children, cases were more likely to have ever been exposed to livestock than controls (AOR = 1.54, 95% CI: 1.03, 2.29). Among women, there was an increase in FCD risk associated with 10 or more years of exposure to livestock (AOR = 2.78, 95% CI: 1.22, 6.33) or 6 or more years of farming (AOR = 2.00, 95% CI: 1.23, 3.25; also adjusted for number of children). Similar findings were not evident among men. Thus, farming and exposure to livestock may be important factors in the development of FCD among women, with this finding further revealed after the confounding effect of parity or number of children is considered.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".