Incidencia de enfermedades reproductivas según raza en el centro de Bogotá D.C
Bibliographic record
Abstract
Con el fin de conocer la incidencia de enfermedades reproductivas en caninos, se realizo un muestreo en los animales que acuden a la Central de Urgencias Veterinarias ubicada en la Ciudad de Bogota. Se tomaron 84 historias clinicas de animales que presentaron problemas reproductivos, identificados en Coker, Labrador, Mestizo, Samoyedo, Siberiano, Beagle, French Poodle. Schnauser. Chihuahua, Bull Dog, Chow Chow, Golden, Shitzu, Pastor Aleman y Pinsht:r. Los principales 19 problemas reproductivos con sus respectivas prevalencias para el ailo 2013 fueron Piometra (26.25%), Distocia (20%), OVH ( 11 .25%), Mastectomia ( 11 .25%), Neoplasia Mamaria (6.25%), Aborto (5%}, Prostatitis (5%), Adenoma (3.75), Mastitis (2.5%), Parto Distocico (2.5%), Adenocarcinoma Mamario ( 1,25%), Muerte Fetal ( 1.25%), Ruptura y Maceracion Fetal (1.25%), Vaginitis Juvenil ( 1.25%), Masa fotravaginal ( 1.25%). Hiperplasia Endometrial Quistica ( 1.25%), Cesaria ( 1.25%), Hemometra ( 1.25%), Absceso Mamario ( 1.25%), al observar 24 perros en el primer trimestre del ailo 2014, solo 5 de 7 enfermedades presentaron una incidencia del 41 % para Piometra, Distocia 20%, Mastectomia 12%, Aborto 4% y Neoplasia Mamaria con el 4%, las 2 restantes como Brucela con el 8% y Endometritis con 8% de prevalencia no fueron positivas en el ailo inmediatamente anterior.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".