The Sino-American Belt Study: Nickel and Cobalt Exposure, Epidemiology, and Clinical Considerations
Bibliographic record
Abstract
BACKGROUND: Nickel and cobalt are common causes of metal allergy. OBJECTIVE: The objective of this study was to investigate nickel and cobalt exposure in belt buckles by testing 701 belts purchased in China and the United States and to consider the prevalence of nickel allergy and its relevance among Chinese patients. METHODS: Seven hundred one belt buckles purchased in China and the United States were tested for nickel and cobalt release. Six hundred thirty-one Chinese patients with suspected allergic contact dermatitis were patch tested and interviewed to determine clinical relevance of results. The Chinese and American literature was reviewed to investigate trends in nickel prevalence over the past decades. RESULTS: Sixty percent (n = 219) of belts purchased in China (n = 365) released nickel, and 0.5% (n = 2) released cobalt; 55.7% (n = 187) in the United States (n = 336) released nickel, and 0.9% (n = 3) released cobalt. Belt dermatitis was a significant clinical finding in 34.8% of Chinese nickel-allergic patients. Literature review suggests increasing nickel allergy prevalence in the United States and China. CONCLUSIONS: Metallic belt buckles are an important source of nickel exposure to consumers. Belts from lowest socioeconomic vendors were more likely to release nickel. Belts with silver color and dark metallic color were more likely to release nickel and cobalt, respectively. Clinical findings show belt dermatitis in China to be a problem.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".