Bibliographic record
Abstract
In this issue of the BJD, the Chronic Hand Eczema epidemiology, Care, and Knowledge of real-life burden (CHECK) study reports on the prevalence of self-reported chronic hand eczema (CHE) among 60 131 adults from general population samples across six countries: Canada, France, Germany, Italy, Spain and the UK.1 Given the historical lack of attention to CHE, a limited number of single-country studies providing CHE prevalence estimates,2,3 and the absence of an International Classification of Diseases (ICD) code for CHE,4 these findings help fill an important gap in hand eczema epidemiology. Notably, accurately estimating the prevalence of CHE is essential for public awareness, guiding healthcare policies and ensuring proper resource allocation,5 which is of particular importance as new treatments for inflammatory skin diseases emerge. The authors administered an online questionnaire to adults across the six countries via online panels, employing quotas and weighting adjustments to ensure representative samples by various demographic parameters. Participants were blinded to the subject of the questionnaire, limiting potential participation bias. Self-reported physician-diagnosed CHE was assessed using the European Society of Contact Dermatitis criteria: having hand eczema continuously for > 3 months or at least two flares in the past 12 months.6
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".