Supplementary Material for: Comparing Two Oral Immunotherapy Strategies for Sesame Allergy: Baked Goods with Sesame Paste Versus Crushed Sesame Seeds
Bibliographic record
Abstract
Background: Sesame allergy is reported to be a major trigger of food induced anaphylaxis and is associated with increased risk of accidental exposure. This study aimed to assess the efficacy and safety of a modified sesame desensitization protocol in children in real-world clinical practice. Methods: Children with a positive skin prick test and a history consistent with an IgE mediated allergy to sesame presenting at the Allergy Clinic of the Montreal Children’s Hospital were recruited. After parents provided informed consent, an initial dose of sesame protein was introduced in the form of baked sesame paste (tahini) muffin or raw sesame seeds under physician supervision. An initial dose of 1/4 teaspoon (5mg sesame protein) was given to the baked group, reaching a maintenance dose of two teaspoons of hummus (600mg protein). In contrast, 75 mg of crushed sesame seeds (approximately 15 seeds) was given to the seeds group, reaching a maintenance dose of one tablespoon (3 g protein) of tahini. Once a maintenance dose was achieved, participants were asked to return to the clinic once a year for five years. Results: The cohort consisted of 76 patients, in which 39 received baked sesame and 37 raw sesame. Considering the two desensitization strategies, using seeds significantly increased the odds of being at a higher reaction severity level by a factor of 7.1 (95% CI: 3.6 - 14.1) compared to baked goods with sesame paste. For both the baked goods and the seeds group, likelihood of severe reactions significantly decreased over time. Conclusion: A modified sesame desensitization protocol using baked sesame paste can be safely used in children with sesame allergy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.888 | 0.323 |
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".