O uso da medicina integrativa no tratamento de desordens hematológicas: Relato de caso
Bibliographic record
Abstract
Hematological disorders are extremely common in the veterinary medical clinic. As they are disorders that affect blood cells in general, there are numerous causes, but the most common are nutrition, parasitic microorganisms and autoimmune diseases. The objective of the present work was to report the case of a 13-year-old Labrador retriever dog with severe hematological disorders and severe anemia, where several differential diagnoses were attempted, but a definitive diagnosis was unsuccessful. Integrative therapies were selected, thus performing an evaluation of the animal and initiating treatment based on its results and laboratory alterations using the following techniques: acupuncture, chromotherapy, Chinese phytotherapy, homeopathy, moxibustion and vitamins. The study allowed us to conclude that the treatment was efficient in increasing cell counts of the hematopoietic system in general, obtaining a significant improvement in the animal's clinical condition.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".