Atopic March: Collegium Internationale Allergologicum Update 2020
Bibliographic record
Abstract
In recent decades, the worldwide prevalence of allergic disease has increased considerably. The atopic march is a model aimed at explaining the apparent progression of allergic diseases from atopic dermatitis (AD) to allergic asthma (AA) and to allergic rhinitis (AR). It hypothesizes that allergic disease begins, typically in children, with the development of AD, then AA, and finally progresses to AR. This theory has been widely studied in cross-sectional and long-term longitudinal studies and it has been found that as prevalence of AD declines, prevalence of AA increases. A similar relationship is reported between AA and AR. The legitimacy of the atopic march model is, however, currently debated. Epidemiological evidence and criticism of longitudinal studies point to an overstatement of the atopic march's prevalence and incorrect mechanisms, opening a discussion for alternative models to better explain the pathophysiological and epidemiological processes that promote this progression of allergic diseases. Albeit, risk factors for the development and progression of allergic disease, particularly AD, are critical in identifying disease progression. Investigating the role of age, severity, family history, phenotype, and genetic traits may give a better indication into the progression of allergic diseases. In addition, studies following patients from infancy into adulthood and a general increase in longitudinal studies would help broaden the knowledge of allergic disease progression and the atopic march.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.011 |
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".