Two Hundred Three Cases of Equine Lymphoma Classified According to the World Health Organization (WHO) Classification Criteria
Bibliographic record
Abstract
Lymphoma is the most common malignant neoplasm in the horse. Single case reports and small retrospective studies of equine lymphomas are reported infrequently in the literature. A wide range of clinical presentations, tumor subtypes, and outcomes have been described, and the diversity of the results demonstrates the need to better define lymphomas in horses. As part of an initiative of the Veterinary Cooperative Oncology Group, 203 cases of equine lymphoma have been gathered from 8 institutions. Hematoxylin and eosin slides from each case were reviewed and 187 cases were immunophenotyped and categorized according to the World Health Organization classification system. Data regarding signalment, clinical presentation, and tumor topography were also examined. Ages ranged from 2 months to 31 years (mean, 10.7 years). Twenty-four breeds were represented; Quarterhorses were the most common breed (n = 55), followed by Thoroughbreds (n = 33) and Standardbreds (n = 30). Lymphomas were categorized into 13 anatomic sites. Multicentric lymphomas were common (n = 83), as were skin (n = 38) and gastrointestinal tract (n = 24). A total of 14 lymphoma subtypes were identified. T-cell-rich large B-cell lymphomas were the most common subtype, diagnosed in 87 horses. Peripheral T-cell lymphomas (n = 45) and diffuse large B-cell lymphomas (n = 26) were also frequently diagnosed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".