Bibliographic record
Abstract
El descubrimiento de formas convenientes para incorporar el Okara en los alimentos podria eliminar una posible fuente unica de destino a pienso y anadiria valor economico a productos menos valorados por su perfil nutricional. 6 A su vez, es sabido que en Argentina el consumo de galletas dulces es sumamente elevado, ya que son mayormente elegidas por la simple razon de saciar el hambre o por habito, segun las principales razones que esgriman los adultos para su consumo. Dentro de America, Argentina ha sido historicamente el principal consumidor con un promedio de 7,4 Kilos, seguido por Brasil con 6,1 kilos, Panama con 6,0 kilos, Estados Unidos con 5,4 kilos, Mexico con 4,3 kilos, Canada con 3,1 kilos y Chile con 2,1 kilos. El consumo anual per capita en la Argentina de Galletas y Bizcochos para el ano 2004 se estima en 5,6 Kg.7. ?Cual es el grado de informacion que tiene la poblacion sobre el Okara y la aceptacion de las galletas enriquecidas hechas a base del mismo? El objetivo general propuesto en el presente trabajo es: • Indagar el grado de informacion que tiene la poblacion acerca del Okara y evaluar la aceptacion de galletas dulces enriquecidas con el mismo en los alumnos de una carrera universitaria de la ciudad de Mar del Plata.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".