Additive Value of Patch Testing Custom Epoxy Materials From the Workplace at the Occupational Disease Specialty Clinic in Toronto
Bibliographic record
Abstract
BACKGROUND: Allergic contact dermatitis (ACD) to epoxy resins is one of the major causes of occupationally induced ACD. Testing of custom epoxy materials from the workplace is often performed to diagnose ACD. OBJECTIVE: The objective of this study was to investigate the additive value of patch testing custom-made epoxy materials. METHOD: We retrospectively analyzed outcomes of 24 patients who were tested to custom epoxy resin materials between January 2002 and July 2011. RESULTS: For 11 patients (46%), the testing of their materials from work had no additional value (negative results). For 13 patients (54%), there was an additional value of testing custom allergens. Of those, 7 patients (54%) had positive reactions to custom epoxy materials that reinforced the test results found with the commercially available allergens, and 6 (46%) patients had positive reactions only to custom epoxy materials. Therefore, for 6 patients (25%), there was a definite additive value of testing custom epoxy materials because the allergy was discovered with custom testing and not with the commercially available allergens. CONCLUSIONS: Because of the high percentage (54%) of patients with additive value of patch testing custom epoxy materials, we think that the inclusion of actual workplace epoxy materials should be strongly considered when patch testing patients with occupational epoxy exposure.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.003 | 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".