Grand challenges for modeling and simulation: simulation everywhere—from cyberinfrastructure to clouds to citizens
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
Modeling & Simulation (M&S) is making successful contributions to different areas in industry and academia. However, there are certain key issues that are preventing the field from addressing larger domains and from achieving wide-scale impact. Formulating these as grand challenges arguably focuses attention on these key issues and may bring a critical mass of effort to bear that could result in a major leap forward. This article is one of several concurrent activities aimed at reinvigorating the debate on grand challenges in M&S. These grand challenges include Big Simulation, human behavior, composability, cloud-based M&S, reproducibility in M&S research and the democratization of M&S. Two themes emerge: the need for large-scale cloud-based cyberinfrastructures for M&S and the democratized access to M&S and its outputs.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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