Nasal food challenge with hen's egg white allergen
Bibliographic record
Abstract
BACKGROUND: Nasal allergen provocation tests are an important part of the diagnostics of allergic diseases triggered by environmental factors. Recently, increased attention has been paid to the potential use of this method in the diagnosis of food allergy. The objective of the study was to evaluate the usefulness of the nasal allergen provocation test in a group of subjects allergic to hen's egg white allergens. METHODS: The material consisted of a group of 57 subjects (32 subjects with hen's egg white allergy and 25 healthy controls). The method consisted in a nasal allergen provocation test carried out with the use of hen's egg white allergen and assessed using the visual analog scale and optical rhinometry as well as by determination of sIgE and tryptase levels in nasal lavage fluid. RESULTS: Subjective nasal symptoms and objective evaluations following the application of 100 µg of hen's egg white allergen revealed a moderately positive nasal mucosal response in optical rhinometry tests (ΔE = 0.34 OD). CONCLUSIONS: Nasal food challenge with hen's egg white allergen is a good diagnostic alternative in the group of food allergy patients. Due to the insufficient number of studies carried out so far, further attempts at standardization of the method are required.
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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) | 0.001 | 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) | 0.002 | 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".