Bibliographic record
Abstract
Agent-based infection-transmission models, which simulate an infection moving through a population, are being employed more frequently by health policy-makers. However, these models present several obstacles to widespread adoption. They are complex entities and impose a high development and maintenance cost. Current tools can be opaque, requiring multidisciplinary collaboration between a modeler and an expert programmer, and another round of translation when communicating with domain experts. In this paper, we describe the use of functional reactive programming (FRP), a programming paradigm created by imbuing a functional programming language with an intrinsic sense of time, to represent agent-based models in a concise and transparent way. We document the conversion of several agent-based models developed in the popular hybrid modeling tool AnyLogic to a representation in FRP. We also introduce Frabjous, a programming framework and domain-specific language for computational modeling. Frabjous generates human-readable and modifiable FRP code from a model specification, allowing modelers to have two transparent representations in which to program: a high-level model specification, and a full functional programming language with an agent-based modeling framework.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".