Prevalencia de babesia spp. en perros (canis familiaris) atendidos en las clínicas veterinarias de la ciudad de Loja y Hospital Docente Veterinario César Agusto Guerrero de la Universidad Nacional de Loja
Bibliographic record
Abstract
The purpose of the following research project was to determine the prevalence of “Babesiosis” in the suspected dogs which ones were treated at the private clinics in the city of Loja and Cesar Augusto Guerrero Hospital of the National University of Loja. A hundred dogs sampling blood in which the saphenous or cephalic vein was removed and blood smears were also performed by puncture of the pinna (peripheral blood) was performed, stained by “Giemsa” and observed under the microscope and those biometrics positive samples was performed. The results got are the following ones: The overall prevalence of Canine Babesiosis is 44%. Considering the age of the highest percentage the obtained results of the dogs one year with 18%, followed by 1-2 years in 11% Canine> 7 years to 6%; the lowest percentage was observed in dogs aged between 3 to 4 years and 5 to 6 with 5% and 4% respectively. Whereas sex was found that the percentage of both males and females is 22% for both genders. As for the race, the highest percentage was in the canine breed Golden Retriever with 80% positive; Shytzu race with 75%; Pitbull race with 67%. The Labrador and Schnauzer breeds with 50%: canine mestizos with 43%; French Poodle breed corresponding to 33%; and Cocker Spaniel breed with 17% infected. As the sector, which showed a higher prevalence was the city of Loja with 43.4%, followed by 42.5% in “Catamayo” Canton, 66.6% in the parish of “Vilcabamba” and 50% in the parish of “Malacatos”. In the hematology to positive canines by Giemsa the main hematologic disorder for red cell anemia is observing 3 types of anemia: Normocytic 34%, 14% and regenerative hyporegenerative 5%; white series for the primary complaint was eosinophilia with 27%, followed by neutrophilia with 20%, 16% leukocytosis, neutropenia and leukopenia 11% 7%; for platelet thrombocytopenia series he found 39%; and no laboratory abnormalities that represent 14%. Finally, the percentage of healthy carriers and patients in which ones of the 44 positive cases, 84% showed correlate symptoms with the presence of “Babesia” in peripheral blood (sick carriers), while 16% were asymptomatic (healthy carriers).
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 | 0.001 | 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 | 0.000 |
| 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".