An?lisis retrospectivo de las historias cl?nicas de una cl?nica veterinaria en Bogot?
Bibliographic record
Abstract
Se presenta un an?lisis de la base de datos de historias m?dicas de una cl?nica veterinaria ubicada en la ciudad de Bogot?, Colombia, con el prop?sito de establecer el orden de importancia de las distintas patolog?as diagnosticadas en los perros desde la perspectiva de su frecuencia, edad de presentaci?n, razas afectadas y g?nero. El estudio abarca 72.248 registros, realizados entre los a?os 1994 y 2004. Los procesos que afectan piel y tegumentos representaron el 24,5% de la casu?stica estudiada, las patolog?as gastroent?ricas el 13,2%, las infestaciones por distintos tipos de par?sitos el 7,9% y los diagn?sticos odontol?gicos el 7,1%. Las dos razas m?s prevalentes son el Labrador retriever con un 23,2% y el French poodle con un 18%, lo cual significa que entre ellas constituyen el 41,2% de las razas atendidas en consulta. A?n cuando el presente trabajo, dadas las caracter?sticas de la metodolog?a utilizada y sobre todo del tipo de muestra, no constituye necesariamente un reflejo exacto de lo que acontece en la ciudad en t?rminos de patolog?as que afectan a los perros, si es un primer referente y la muestra estudiada es amplia en n?mero de casos y tiempo de observaci?n
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".