The Canadian Journal of Diagnosis / February 200370
Bibliographic record
Abstract
Winter is here and with its arrival the cen-trally heated air indoors worsens skin dry-ness, leading to a perturbed epidermal barrier and increased incidence of atopic dermatitis (AD). AD is an inflammatory skin disease primarily in infants and children with a personal or family history of atopy, such as dermatitis, seasonal rhinitis, allergies, or asthma (Figure 1).1 Disease severity improves with age in most patients. The prevalence in highly developed socioeconomic societies has been increasing from 2 % to 15 % of children since the 70s.1,2 Eczema, the meaning derived from “boiling, ” is used by many people interchangeably with dermatitis, however, it should be restricted to acute vesicular dermatitis. What are the diagnostic criteria? Atopic dermatitis has been called “the itch that rashes. ” Pruritus is primordial and leads to scratching or rubbing, which in turn creates acute excoriations or chronic lichenifi-cation. Characteristically, the face and extensor surfaces of the extremities are affected in infancy, whereas the flexures become involved in older children and adults. In this article: 1. What are the diagnostic criteria? 2. What factors contribute to AD? 3. What about immunologic abnormalities? 4. How is AD diagnosed? 5. Are there tests for AD? 6. What is differential diagnosis of AD? 7. How do you treat AD? 8. What about topical corticosteroids? 9. What about antibiotics? 10. Is there systematic therapy?
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.334 | 0.133 |
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".