Implementación de un programa de buenas prácticas de manufactura en el centro de acopio y transformación de la Fundación Chankuap de la ciudad de Macas-Morona Santiago.
Bibliographic record
Abstract
En la actualidad las empresas son más competitivas, enfrentan nuevos mercados y los \nconsumidores exigen cada vez más atributos de calidad en los productos que \nadquieren, siendo una característica esencial e implícita la inocuidad (Ramírez, I., \n2011). \nLa Fundación Chankuap es una Organización No Gubernamental (ONG) que busca \nla prestación de servicios de desarrollo social integral en la región amazónica. Cuenta \ncon un Centro de Acopio y Transformación en donde se producen alimentos, \ncosméticos y fitofármacos, empleando para esto tecnología apropiada y las mejores \nespecies cultivadas orgánicamente en la selva amazónica por comunidades indígenas \nShuar, Achuar y Colono Mestizos de las provincias de Morona Santiago y parte del \nPastaza. La Fundación colabora con estos grupos vulnerables mediante la autogestión \ny solidaridad (Bolsa Amazonía-Cooperación y Negocios Sostenibles, s.f.; Fundación \nChankuap, 2006, Fundación Chankuap, s.f.b). \nComprometida con el mercado nacional e internacional la Fundación debe ofrecer \nproductos sanos, inocuos y de calidad, para satisfacer y cumplir con las expectativas \nde sus clientes.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".