Cutaneous nonepitheliotropic B-cell lymphoma in a Golden retriever
Bibliographic record
Abstract
The vast majority of cutaneous canine nonepitheliotropic lymphomas are of T cell origin.Nonepithelial Bcell lymphomas are extremely rare.The present case report describes a 10-year-old male Golden retriever that was presented with slowly progressive nodular skin lesions on the trunk and limbs.Histopathology of skin biopsies revealed small periadnexal dermal nodules composed of rather pleomorphic round cells with round or contorted nuclei.The diagnosis of nonepitheliotropic cutaneous B-cell lymphoma was based on histopathological morphology and case follow-up, and was supported immunohistochemically by CD79a positivity. SAMENVATTINGHet overgrote deel van de cutane caniene niet-epitheliotrope lymfoma's is van T-celorigine.Niet-epitheliotrope B-cellymfoma's zijn zeer zeldzaam.Dit is een casereport van een 10-jaar oude Golden retriever aangeboden met traaggroeiende nodulaire gezwellen in de huid van de romp en ledematen.Histopathologisch werden kleine periadnexale dermale nodulen, samengesteld uit pleomorfe rondcellen met een ronde of niervormige kern, aangetroffen.De diagnose van een niet-epitheliotroop lymfoma werd gesteld aan de hand van de histopathologie en caseopvolging en ondersteund door CD79a-positiviteit via immunohistochemie.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".