Documentary research of clinical and epidemiological aspects of lymphoma in dogs treated at the federal rural university of Rio de Janeiro
Bibliographic record
Abstract
Lymphomas, malignant neoplasms that originate in the lymphocytes, have a high incidence in domestic animals. This paper aimed to describe the clinical and epidemiological findings of 200 cases of canine lymphoma evaluated over nine years (2011–2019) at the Oncology Service of the Veterinary Hospital at The Federal Rural University of Rio de Janeiro. A majority of mixed-breed canines (84/200-42%) were observed, followed by the Labrador Retriever, Pitbull, and Rottweiler with similar incidence (15/200-7.5%). The average age was 7.7 years and the most affected canines were aged approximately 3 and 11 years old (146/200-73%). As for the anatomical classification, the cases classified as multicentric (131/200-65,5%) were the most common, followed by cases of the cutaneous form (44/200-22%), alimentary form (7/200 - 3.5%), mediastinal form (5/200-2.5%), and extranodal form (16/200-6,5%). Among extranodal cases were described cases of ocular involvement (5/200-2.5%), oral cavity involvement (4/200-2%), cardiac involvement (3/200-1.5%), and pulmonary involvement (1/200-0.5%). The clinical manifestation observed was related to the affected region in the different anatomical forms. More studies of this nature are needed to profile the disease presentation and contribute to clinical identification and diagnosis.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".