A Different Type of Second Wave: A Predicted Increase in Personal Protective Equipment–Related Allergic Contact Dermatitis as a Result of Coronavirus Disease 2019
Bibliographic record
Abstract
DermatitisVol. 31, No. 5 LettersA Different Type of Second Wave: A Predicted Increase in Personal Protective Equipment–Related Allergic Contact Dermatitis as a Result of Coronavirus Disease 2019Lauren K. Rangel and David E. CohenLauren K. RangelThe Ronald O. Perelman Department of Dermatology, NYU Grossman School of Medicine, NY .Search for more papers by this authorEmail the corresponding author at [email protected] and David E. CohenThe Ronald O. Perelman Department of Dermatology, NYU Grossman School of Medicine, NY .Search for more papers by this authorEmail the corresponding author at [email protected]Published Online:1 Oct 2020AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookXLinked InRedditEmail View article"A Different Type of Second Wave: A Predicted Increase in Personal Protective Equipment–Related Allergic Contact Dermatitis as a Result of Coronavirus Disease 2019." Dermatitis, 31(5), pp. e54–e55FiguresReferencesRelatedDetails Volume 31Issue 5Oct 2020 Information© 2020 American Contact Dermatitis Society. All Rights Reserved.To cite this article:Lauren K. Rangel and David E. Cohen.A Different Type of Second Wave: A Predicted Increase in Personal Protective Equipment–Related Allergic Contact Dermatitis as a Result of Coronavirus Disease 2019.Dermatitis.Oct 2020.e54-e55.http://doi.org/10.1097/DER.0000000000000650Published in Volume: 31 Issue 5: October 1, 2020 PDF 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".