Clostridium difficile: un patógeno emergente en Medicina Veterinaria
Bibliographic record
Abstract
Clostridium difficile es un bacilo Gram positivo esporulado que forma parte de la microbiota intestinal del hombre y animales domesticos y es una causa establecida de diarrea y colitis pseudomembranosa. Este microorganismo es uno de los patogenos nosocomiales, mas frecuentes en el mundo, existiendo una correlacion positiva de esta infeccion con el empleo de antibioticos. Debido a que las cefalosporinas de tercera generacion, clindamicina y amoxicilina son antibioticos de amplio uso en los hospitales, se asocian con el mayor riesgo de desarrollo de diarrea asociada a antimicrobianos. El diagnostico de laboratorio de C. difficile es efectuado en infecciones humanas y animales por la demostracion de las toxinas del microorganismo en muestras de deposiciones, mediante tecnicas inmunologicas. C. difficile sobrevive mal en deposiciones, lo que limita la sensibilidad del cultivo. Desde 2002 se ha informado en Canada, Estados Unidos. Gran Bretana y Holanda la aparicion y diseminacion de una cepa epidemica, portadora del toxinotipo III, ribotipo 027. Esta cepa ha demostrado ser hipervirulenta, causando elevada mortalidad en pacientes hospitalizados. Este hallazgo demuestra el potencial que tiene esta bacteria para cambiar su virulencia, alertando ante su posible aparicion en poblaciones animales, como asimismo en Sud America. Un control racional en el uso de antibioticos puede ayudar al control de la diseminacion de este organismo.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".