A time-expanded network for the biomedical sample transportation problem
Bibliographic record
Abstract
En esta investigacion, se propone una nueva formulacion sobre una red expandida en el tiempo para el problema de transporte de muestras medicas. El problema de transporte de muestras medicas es un problema de ruteo de vehiculos que surge en el contexto de la logistica en salud. La dificultad de este problema de transporte esta relacionada con la vida util de la muestra porque la duracion de una ruta esta limitada por el tiempo disponible para completar el transporte de la muestra antes de que perezca. Para probar la calidad y el comportamiento de la formulacion expandida en el tiempo, se realizan experimentos en un conjunto de instancias inspiradas en la operacion de la red de laboratorios de Quebec bajo la administracion del Ministere de la Sante et des Services sociaux (Ministerio de Salud y Servicios Sociales). Los resultados exponen la conveniencia de utilizar una red expandida en el tiempo para modelar el problema de transporte de muestras medicas..
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".