Bibliographic record
Abstract
BACKGROUND: Few studies have considered garlic odour as a socially important outcome of occupational tellurium (Te) exposure or concurrent exposures, and most known guidelines focus on other signs and symptoms (e.g. weight loss and somnolence). This study considers workers exposed to tellurium and selenium (Se) at an Ontario, Canada silver refinery. AIMS: To establish the relation of urinary tellurium concentrations to reporting garlic odour, while considering other work-related factors such as concurrent urinary selenium concentrations. METHODS: Historical surveillance records of urinary analyses for tellurium and selenium concentrations (μmol Te or Se/mol creatinine in urine) and symptom self-reports were used. Records were available from December 1986 to June 2002. Logistic regression models were fitted using age at sampling, tellurium and selenium urine concentration and duration of employment. Individual main effects were age adjusted and the final model was fitted for tellurium and selenium urine concentration and duration of employment. RESULTS: Urinary tellurium concentration was significantly associated with garlic odour reporting (odds ratio = 1.74, 95% confidence interval 1.01-2.97, P < 0.05). Furthermore, the likelihood of reporting garlic odour rose as workers reached urinary tellurium concentrations >1 μmol/mol creatinine. CONCLUSIONS: Tellurium urinary concentrations of <1 μmol/mol creatinine appear to limit, but not eliminate, the likelihood of reporting garlic odour. Future studies should consider the effect of concurrent selenium exposure as well as other workplace factors and hygiene.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".