Estudo retrospectivo dos exames histopatológicos realizados em cadelas com tumores mamários em hospital veterinário
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Neoplasia is an abnormal mass of tissue with atypical growth and without biological purpose that can reach any tissue of the animal organism. However, in dogs, breast neoplasms are more frequent, especially in bitches aged over 8 years. Therefore, it is important to know epidemiological aspects regarding this disease for the best therapeutic choice and, consequently, for the success of the treatment. Thus, the present study aimed to carry out a survey of the reports of histopathological exams performed at the Veterinary Hospital of Uberaba from January 2016 to March 2018 and to verify the most affected breeds, the tumor characteristics, such as malignancy, aspects of the neoplasm, metastatic index and recurrences, the reports of imaging exams and the most frequent hematological changes. Among the most affected animals in this period are the mixed breed dogs, Poodle, BassetHound and Labrador. Elderly animals over 8 years old had higher prevalence (84.8%) compared to adult dogs. The most important hematological changes due to the number of occurrences were thrombocytosis and normochromic normocytic anemia. Breast carcinoma and mixed mammary tumor were the most frequent 12.0 and 27.2% respectively. With this study we saw the need for a good staging of neoplasms, assisting the clinician in the therapeutic decision, improving the prognosis of cancer patients.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 it