Prevalencia de Toxoplasmosis en Caninos Domésticos (canis familiaris), en el Barrio San Sebastián, Cantón Latacunga
Bibliographic record
Abstract
The present investigation was carried out in the San Sebastián neighborhood, Latacunga canton, with the taking of 81 samples in canines. The objectives of the work is to determine the prevalence of toxoplasma gondii in domestic canines, according to the clinical assessment of age, sex, race establishing positive or negative cases; proceeding to elaborate a management and prevention instructions; finalizing with the socialization of the results to the residents of the area. \nFor your diagnosis, an indirect ELISA kit was tested in the Tumbaco Agrocalidad laboratory - Quito, with the help of the local pet owners, opening clinical files with the data received from them, which facilitated the extraction of blood samples in an amount of 3 ml to 5 ml, being placed in a red cap vacutainer tube (without anticoagulant) for the corresponding obtaining of the serum and being sent under the required standards, to process them and emit positive and negative results. \nTherefore, the prevalence of toxoplasma gondii in the study area is determined with representative values of 13.6%; distributed according to the age of 1 to 11 months with 5.9%; from 1 to 5 years 18.5%; according to sex, in females 12.5%, in males 14.3%; the race with the highest prevalence of positive cases is 20.6% in mestizo dogs, followed by the labrador and German shepherd breed 33.3%, Golden dogs 20%
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".