A combined discrete-continuous simulation model for analyzing train-pedestrian interactions
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
Computer simulation has defined itself as a reliable method for the analysis of stochastic and dynamic complex systems in both academic and practical applications. This is largely attributed to the advent and evolution of several simulation taxonomies, such as, Discrete Event Simulation, Continuous Simulation, System Dynamics, Agent-Based Modeling, and hybrid approaches, e.g., combined discrete-continuous simulation, etc. Each of these simulation methods works best for certain types of problems. In this paper, a discrete-continuous simulation approach is described for studying train and pedestrian traffic interactions for purposes of decision support. A practical operations problem related to commodity train operation within two small towns in Alberta, Canada, is then used to demonstrate the implementation of the approach within the Simphony.NET simulation system. Simulation results generated are presented.
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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 | 0.001 |
| 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 | 0.001 |
| 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