Quesos maduros, potencial económico para la Provincia del Valle de Ubaté
Bibliographic record
Abstract
La provincia del Valle de Ubaté se encuentra ubicada en el departamento de Cundinamarca, goza de un clima frío que favorece la producción de pastos, de allí la especialización en producción lechera, elaboración de productos lácteos y comercialización de los mismos, sin embargo aún cuenta con algunos segmentos o productos que han sido poco explotados como es el caso del queso maduro, éste artículo busca motivar a los productores, comercializadores y transformadores de estos productos para ingresar a un nuevo segmento en el mercado lácteo, beneficiándose del tratado de libre comercio firmado con Canadá, que elimina los aranceles para los productos lácteos y de ésta forma cambiar los paradigmas de producción de la provincia. ABSTRACT The province of Valle de Ubaté is located in the department of Cundinamarca, it enjoys a cold climate that favors the production of pastures, hence the specialization in dairy production, processing of dairy products and marketing of the same, however still has some segments or products that have been little exploited as is the case of mature cheese, This article seeks to motivate producers, marketers and processors of these products to enter a new segment in the dairy market, benefiting from the free trade agreement signed with Canada, which eliminates tariffs for dairy products and thus change the production paradigms of the province.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".