Modelo de aproximación lineal para la medición de resiliencia en cadenas de suministro
Bibliographic record
Abstract
La identificacin del nivel de resiliencia de un sistema es fundamental para la toma de decisiones en la prevencin y planeacin de estrategias de recuperacin ante fallas que lo puedan afectar. Este artculo busca disear una mtrica de aproximacin lineal para la medicin de resiliencia en cadenas de suministro ante eventos disruptivos inesperados. Las mtricas tradicionales de resiliencia simplifican el comportamiento de un sistema despus de la ocurrencia de una falla, dificultando que las mediciones se puedan realizar en escenarios de fallas de mayor complejidad. Una mtrica general de resiliencia es desarrollada y validada en un caso simulado de una cadena de suministro de dos eslabones con interrupciones en el proceso de transporte. Los resultados confirman que las mtricas de resiliencia tradicionales sobreestiman los niveles de resiliencia del sistema, debido a la inhabilidad de modelar diferentes escenarios de eventos disruptivos. Los resultados del caso simulado sugieren que la nueva mtrica mejora la estimacin de resiliencia en comparacin con las mtricas lineales previas y, adicionalmente provee la flexibilidad necesaria para ser utilizada en otros tipos de sistema diferentes a cadenas de suministro.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".