Evaluación de la aplicabilidad de las normas sanitarias andinas en el comercio de animales terrestres y sus productos, con relación a enfermedades exóticas de los animales de importancia para la subregión, para el período 2010 – 2017
Bibliographic record
Abstract
The purpose of the study was to evaluate the applicability of the Andean health standards related to exotic diseases of importance in the andean subregion in the trade of animals and their products. From the carried out analysis, the largest volume of imports was poultry, pigs and cattle. The Andean regulations had variable coverage. From the imports of animals and their products, the main countries which reported exotic diseases were identified as Belgium, China, United States of America, Canada, Chile and Italy: and the customs risk tariff were identified with a total for cattle of 15 goods, equids 2 goods, sheep-goats 6 goods, pigs 6 goods and birds 15 goods. The study showed 100% compliance with the Andean standards for bees and lagomorphs, 62.5% for cattle, 59.5% for birds, 80.6% for sheep - goats, 76.9% for pigs, and 50% for equids. The results suggested that the Member Countries and the SGCAN should establish a review and adjustments of requirements related to exotic diseases and custom tariff, to ensure that Andean regulation are observed, in safeguarding public and animal health of the subregion.
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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".