Prevalence of poultry diseases in Gazipur district of Bangladesh
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Bibliographic record
Abstract
This study was designed with a view to investigate the prevalence of poultry diseases in Gazipur district of Bangladesh. A total of 679 poultry birds (313 layers, 338 broilers and 28 cockrels) either dead or live were brought for diagnosis of diseases at Gazipur Sadar Upazilla Veterinary Hospital. The diseases were diagnosed on the basis of history, clinical signs and post-mortem findings. The diseases encountered in layers were bacterial diseases 52.29% (salmonellosis 38.56%, colibacillosis 6.7%, fowl cholera 4.79% and necrotic enteritis 1.60%), viral diseases 23.95% (avian influenza 2.56%, Newcastle disease 16.61%, infectious bronchitis 3.19% and avian leucosis 0.64%), mycoplasmal disease (mycoplasmosis 14.70%) and protozoal disease (coccidiosis 5.75%). Salmonellosis was most prevalent disease in age group of >20 weeks, while Newcastle disease most common in 8 to 20 weeks of age group. In case of broiler, bacterial diseases 28.99% (salmonellosis 21.30% and colibacillosis 7.69%), viral diseases 53.24% (infectious bursal disease 28.99%, Newcastle disease 8.87% and infectious bronchitis 15.38%), mycoplasmal disease (mycoplasmosis 7.1%) and protozoal disease (coccidiosis 6.5%). In cockrels, the most prevalent disease was colibacillosis 35.71% followed by salmonellosis 28.57%, Newcastle disease 14.28% and mycoplasmosis14.28%. So among the diseases, salmonellosis is most prevalent disease followed by infectious bursal disease and mycoplasmosis in different kinds of poultry of Gazipur district of Bangladesh.Asian J. Med. Biol. Res. March 2016, 2(1): 107-112
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it