Comparative study of different haematological and biochemical parameters in normal German Shepherd and Labrador dogs
Bibliographic record
Abstract
Present study was conducted to evaluate the haematological and biochemical parameters in Labrador and German shepherd dogs. Total 16 healthy privately owned Labrador (n=8) or German shepherd dogs (n=8); 2-5 yrs. of age, weighing around 20 ± 5 kg, with body condition scores of 3 on a 1 to 5 scale residing in Akola city were selected. Blood sample (4 ml) was collected from each dog in plain vacutainer as well as in EDTA vials from cephalic or saphenous vein by using 21 gauze needles. After collection, blood in the plain vials was allowed to clot; serum was separated by centrifugation at 5000 g for 10 minutes and stored at -20 ˚C until further analysis of biochemical parameters. Haematological analysis was carried out within 20 minutes of blood collection. The mean haematological values recorded in German shepherd and Labrador dogs such as PCV, Haemoglobin, platelet count, total erythrocyte count, total leucocyte count, differential leukocyte count MCV, MCHC and MCH were in normal physiological limit and showed non-significant difference between the two breeds. The mean biochemical values recorded such as Total cholesterol, Triglyceride, Total protein and BUN concentration were in normal physiological limit. The Total cholesterol and Triglyceride concentration showed significant difference among the two breeds, whereas Total protein and BUN concentration showed non-significant difference between the two breeds. The present study revealed that the German shepherd and Labrador breeds of dogs showed the non-significant difference in haematological values and biochemical values except total cholesterol and triglyceride.
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 | 0.000 |
| 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 | 0.000 |
| 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".