Haemato-biochemical Changes in Natural Cases of Canine Babesiosis
Bibliographic record
Abstract
Incidence of severe anemia due to babesiosis in dogs resulting in death in a short time of illness is on the increase in Punjab, during last few decades due to introduction of exotic breeds like Grey Hound, German shepherd, Doberman, Labrador and others.In the present study the hematological and biochemical changes in blood samples obtained from 4 dogs naturally infected with Babesia were evaluated.The dogs were presented to the Department of Veterinary Clinical Services Complex, GADVASU, Ludhiana from August 2008 to April 2009.The evaluation included Hemoglobin (Hb), Red Blood Cell count (RBC), Packed Cell Volume (PCV), Mean Corpuscular Volume (MCV), Mean Corpuscular Hemoglobin Concentration (MCHC), leucocyte counts, platelet counts and reticulocyte counts.The serum biochemistry included Blood Urea Nitrogen (BUN), creatinine, total protein, albumin, bilirubin, Aspartate amino Transferase (AST), Alanine amino Transferase (ALT), Alkaline Phosphatase (ALP), The hematological findings in most of these dogs were normocytic normochromic anemia and thrombocytopenia.The total and differential leukocyte counts were not specific.Biochemical values were within normal ranges but serum biochemistry varied for each dog.This study indicated that Babesia infection in dogs apparently caused anemia and thrombocytopenia, while other clinical values did not change.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".