Detection And Distribution Of Gastrointestinal Nematodes In Cows And Buffaloes And Their Fecal Egg Count Per Gram For Parasitic Burden In KPK, Pakistan
Bibliographic record
Abstract
The GIT parasites are the main constrain for the decrease productivity of the cattle and buffaloes. The current study was conducted to evaluate the detection and distribution of gastrointestinal nematodes in cows and buffaloes and their fecal egg count per gram for parasitic burden in Khyber Pakhtunkhwa, Pakistan. In the current study, a total of 330 samples were examined. The overall prevalence of gastrointestinal nematodes was 42.12%. The rate of infection in cows was noted to be higher 44.45% than in buffaloes 39.33%. The gastrointestinal nematode infections were lower in female than male animal i.e. 40.76% and 47.14%, respectively. The result regarding gender was noted to be similar for both cows and buffaloes. The young animals were recorded to be more susceptible to gastrointestinal infection with nematode parasites 46.15% as compared to adults 39.50%. Moreover, the prevalence of gastrointestinal Nematodes was higher in months of July-august followed by May-June, September-October and March-April. The prevalence in grazing animals was higher 58.99% than stall feeding 41.01%. Among the nematode species Trichostrongylus species were more common followed by Haemonchus, Ostertagia, Bunostomum, Toxocara, Strongyloid, Nematodiurus, Trichuris and Coopeia, i.e. 14.84%, 10.90%, 9.39%, 8.18%, 7.27%, 6.66%, 4.24%, 3.93% and 3.03%, respectively. The overall egg per gram was 2.01. The analysis of egg per gram showed high value for buffaloes 2.10 than cows 1.89. The young animals were found with more parasitic burden of 2.26 eggs per gram than 1.77 eggs per gram in adults. The grazing animals were also noted to be at great risk of being infected with a high load of parasites as compared to stall fed i.e. 2.30 egg per gram and 1.67 eggs per gram, respectively.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".