A generic and flexible simulation-based analysis tool for EMS management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Emergency medical services (EMS) are dedicated to provide urgent medical care to any person requiring it and to ensure their transport to a hospital or care facility, if required. Moreover, in many contexts, EMS also have to provide transportation services for patients need to go from one hospital to another or between their home and the hospital. For such organisations, efficient strategies for managing the ambulance fleet at their disposal have to be selected, but the highly random and dynamic nature of the system under study makes this a challenging task. Most of the published studies which have considered these issues have done it focusing on a specific EMS context, one city or one territory for instance. However, it is possible to identify several common characteristics and processes from one EMS context to another. This is the purpose of the generic discrete event simulation-based analysis tool proposed here, which can be adapted to a wide range of EMS contexts. In particular, it explicitly considers the two types of tasks that can compose the mission of an EMS: serving emergency requests and providing transports between care units/hospitals/patients’ homes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it