Patch-Test Results of an Academic Department in Izmir, Turkey
Bibliographic record
Abstract
BACKGROUND: With the development of industry, the numbers of allergens are increasing, and the frequency of these allergens show variations from country to country. The aim of this retrospective study was to determine the distribution of patch-test results by age, gender, and occupation in our region. METHODS: In a retrospective study, the patch-test results of 3,017 patients were evaluated. The results were statistically examined by frequency of age, gender, and occupation. Chi-square and Fisher exact tests were used for statistical evaluation. RESULTS: Of 3,017 patients, 1,975 (65.5%) were female and 1,042 (34.5%) were male. Their ages ranged from 5 to 85 years (mean, 40.38 +/-14.69 years). In 944 (31.3%) patients, at least one positive reaction to an allergen was observed. The allergens that most commonly caused positive reactions were nickel sulfate (12.2%), cobalt chloride (7.1%), potassium dichromate (5.6%), and balsam of Peru (2.8%). Balsam of Peru and nickel were the most common allergens in female patients older than 45 years and in female patients younger than 35 years, respectively. CONCLUSIONS: Nickel sulfate and cobalt chloride were found to be the most common allergens. The most frequently seen allergens were nickel sulfate (in females) and fragrance (in males).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".