Allergen immunotherapy on the way to product-based evaluation—a WAO statement
Bibliographic record
Abstract
Allergen immunotherapy (AIT) is widely used in clinical practice for patients with moderate to severe allergic rhinitis due to inhalant allergens and may be delivered via subcutaneous (SCIT) and sublingual routes (SLIT). However, the quality of evidence for individual AIT products is very heterogeneous, and extensions of overall conclusions ("class effects") on the efficacy and disease-modifying effects to all AIT products are unjustified. In contrast, each product needs to be evaluated individually, based on available study results, to justify efficacy and specific claims on sustained and disease modifying effects per allergen and targeted patient group (children vs. adults, allergic rhinitis vs. asthma). WAO intends to support the current development to evidence-based AIT, which ultimately will lead to a more efficacious treatment of allergic patients and the appropriate recognition of AIT.
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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 | 0.084 | 0.081 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.068 | 0.039 |
| Insufficient payload (model declined to judge) | 0.004 | 0.006 |
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".