Sesame allergy: current perspectives
Bibliographic record
Abstract
Sesame is an important global allergen affecting ~0.1% of the North American population. It is a major cause of anaphylaxis in the Middle East and is the third most common food allergen in Israel. We conducted a systematic review of original articles published in the last 10 years regarding the diagnosis and management of sesame allergy. Skin prick testing appears to be a useful predictor of sesame allergy in infants, although data are less consistent in older children and adults. The diagnostic capacity of serum-specific immunoglobulin E is poor, especially in studies that used oral food challenges to confirm the diagnosis. Double-blind, placebo-controlled food challenge thus remains the diagnostic gold standard for sesame allergy. The cornerstone of sesame allergy management is allergen avoidance, though accidental exposures are common and patients must be prepared to treat the consequent reactions with epinephrine. Novel diagnostic and treatment options such as component-resolved diagnostics, basophil activation testing, and oral immunotherapy are under development but are not ready for mainstream clinical application.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".