Successful Treatment of Atopic Hand and Foot Eczema with Oral Janus Kinase 1 Inhibition
Bibliographic record
Abstract
Dermatitis®Ahead of Print LetterSuccessful Treatment of Atopic Hand and Foot Eczema With Oral Janus Kinase 1 InhibitionSebastian Sitaru, Sarah Preis, and Bernadette EberleinSebastian SitaruE-mail Address: [email protected]https://orcid.org/0000-0001-7324-9139Department of Dermatology and Allergy, Technical University of Munich, School of Medicine, Munich, GermanySearch for more papers by this author, Sarah PreisDepartment of Dermatology and Allergy, Technical University of Munich, School of Medicine, Munich, GermanySearch for more papers by this author, and Bernadette EberleinDepartment of Dermatology and Allergy, Technical University of Munich, School of Medicine, Munich, GermanySearch for more papers by this authorPublished Online:19 Jan 2023https://doi.org/10.1089/derm.2022.0030AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"Successful Treatment of Atopic Hand and Foot Eczema With Oral Janus Kinase 1 Inhibition." Dermatitis®, , pp. FiguresReferencesRelatedDetails Volume 0Issue 0 Information© 2021 American Contact Dermatitis Society. All Rights Reserved.To cite this article:Sebastian Sitaru, Sarah Preis, and Bernadette Eberlein.Successful Treatment of Atopic Hand and Foot Eczema With Oral Janus Kinase 1 Inhibition.Dermatitis®.ahead of printhttp://doi.org/10.1089/derm.2022.0030Online Ahead of Print:January 19, 2023PDF download
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".