Análisis de peligro y puntos críticos de control: Su relación con la inocuidad de los alimentos Hazard analysis and critical control points. Its relation with food inocuity
Bibliographic record
Abstract
Se hace una revisión bibliográfica del sistema de análisis de peligro y puntos críticos de control (APPCC) teniendo en cuenta sus antecedentes históricos, así como la descripción del sistema (aplicable a cualquier eslabón de la cadena alimentaria), basado en la secuencia lógica y en la aplicación del árbol de decisiones para determinar los puntos críticos de control (PCC). Se hace referencia a su importancia como, por ejemplo, que detecta cualquier alteración desde el punto de vista biológico, físico y/o químico sin tener que esperar el producto final. Se mencionan inconvenientes tales como contar con personal capacitado, recursos, etcétera. Una de las razones básicas para la implantación del sistema es que se obtiene un alimento apto para el consumo humano. De los beneficios más importantes se puede citar que se reducen las reclamaciones y devoluciones. En este momento está implantado en países como Estados Unidos, Canadá, la Unión Europea y otros. A bibliographic review of the system of analysis of danger and critical control points (ADCCP) is made taking into account its historical background, as well as the description of the system (applicable to any link of the food chain), based on the logical sequence and on the application of the tree of decisions to determine the critical control points (CCP). Reference is made to its importance, as for example, that it detects any alteration from the biological, physical and/or chemical point of view without having to wait for the final product. Inconveniences, such as having to have a trained personnel, resources, etc. are mentioned. One of the basic reasons for the introduction of the system is the obtention of food apt to human consumption. The reduction of claims and devolutions are among the most important benefits. It has already been implemented in the United States, Canada, the European Union, and others.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".