Diagnostic and therapeutic challenges in erythema elevatum diutinum
Bibliographic record
Abstract
AMA Milewska J, Chmielińska P, Czuwara J, et al. Diagnostic and therapeutic challenges in erythema elevatum diutinum. Dermatology Review/Przegląd Dermatologiczny. 2023;110(6):711-715. doi:10.5114/dr.2023.138880. APA Milewska, J., Chmielińska, P., Czuwara, J., Kryst, A., Jasińska, M., & Rakowska, A. et al. (2023). Diagnostic and therapeutic challenges in erythema elevatum diutinum. Dermatology Review/Przegląd Dermatologiczny, 110(6), 711-715. https://doi.org/10.5114/dr.2023.138880 Chicago Milewska, Justyna, Paulina Chmielińska, Joanna Czuwara, Alicja Kryst, Magdalena Jasińska, Adriana Rakowska, and Małgorzata Olszewska et al. 2023. "Diagnostic and therapeutic challenges in erythema elevatum diutinum". Dermatology Review/Przegląd Dermatologiczny 110 (6): 711-715. doi:10.5114/dr.2023.138880. Harvard Milewska, J., Chmielińska, P., Czuwara, J., Kryst, A., Jasińska, M., Rakowska, A., Olszewska, M., and Rudnicka, L. (2023). Diagnostic and therapeutic challenges in erythema elevatum diutinum. Dermatology Review/Przegląd Dermatologiczny, 110(6), pp.711-715. https://doi.org/10.5114/dr.2023.138880 MLA Milewska, Justyna et al. "Diagnostic and therapeutic challenges in erythema elevatum diutinum." Dermatology Review/Przegląd Dermatologiczny, vol. 110, no. 6, 2023, pp. 711-715. doi:10.5114/dr.2023.138880. Vancouver Milewska J, Chmielińska P, Czuwara J, Kryst A, Jasińska M, Rakowska A et al. Diagnostic and therapeutic challenges in erythema elevatum diutinum. Dermatology Review/Przegląd Dermatologiczny. 2023;110(6):711-715. doi:10.5114/dr.2023.138880.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".