Localized Nummular Dermatitis of the Bilateral Breasts Developing 4 Months after Breast Reduction Surgery
Bibliographic record
Abstract
Dermatitis®Ahead of Print LetterLocalized Nummular Dermatitis of the Bilateral Breasts Developing 4 Months After Breast Reduction SurgeryJohn Miller and William JamesJohn MillerCollege of Medicine, Sidney Kimmel Medical College, Philadelphia, PA USA E-mail Address: john.miller@students.jefferson.eduhttps://orcid.org/0000-0001-9132-5254J.M. was involved in investigation (equal), writing—original draft (lead), and writing—reviewing and editing (equal). W.J. was involved in conceptualization (lead), investigation (equal), supervision (lead), and writing—reviewing and editing (equal).Search for more papers by this author and William JamesDepartment of Dermatology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USAJ.M. was involved in investigation (equal), writing—original draft (lead), and writing—reviewing and editing (equal). W.J. was involved in conceptualization (lead), investigation (equal), supervision (lead), and writing—reviewing and editing (equal).Search for more papers by this authorPublished Online:24 Jan 2023https://doi.org/10.1089/derm.2022.0008AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"Localized Nummular Dermatitis of the Bilateral Breasts Developing 4 Months After Breast Reduction Surgery." Dermatitis®, , pp. –FiguresReferencesRelatedDetails Volume 0Issue 0 Information© 2021 American Contact Dermatitis Society. All Rights Reserved.To cite this article:John Miller and William James.Localized Nummular Dermatitis of the Bilateral Breasts Developing 4 Months After Breast Reduction Surgery.Dermatitis®.ahead of printhttp://doi.org/10.1089/derm.2022.0008Online Ahead of Print:January 24, 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.024 | 0.004 |
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".