Retrospective Analysis of Clinical Histories From a Veterinary Clinic of Bogot?
Bibliographic record
Abstract
An analysis of the data base of medical histories of a located veterinary clinic in Bogota, Colombia is presented to establish the order of importance of the different diagnosed pathologies in the dogs taking into account their frequency, age of presentation, breeds affected and gender. The study includes 72,248 registries. It was carried out between 1994 and 2004. The processes that affect skin and tegumentos represented 24.5% of the studied cases, gastroent?ricas pathologies 13,2%, odontol?gicos infestations by different types from parasites 7.9% and diagnoses 7,1%. The two more prevalent breeds are the Labrador retriever with 23,2% and the French poodle with 18%, which means that among them it makes up for 41.2% of the races taken care of in consultation. Even though the present work, given the characteristics of the used methodology and mainly of the type of sample, does not constitute an exact reflection necessarily of what occurs in the city in terms of pathologies that affect the dogs, it is a first reference and the studied sample is ample in number of cases and time of observation.
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How this classification was reachedexpand
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".