Modeling Airport Check-In and Security Procedures Using SimFC
Bibliographic record
Abstract
Simulator For Construction (SimFC) is a construction-related simulation platform which allows for modeling of various construction processes in a controllable and repeatable manner. These processes can vary in complexity and size involving various resource requirements and time constraints. However, SimFC is also a versatile general purpose simulator which allows users to easily model almost all entity-relationship based systems using the elements provided in the visual environment. On the other hand, planning for airport human resources is often a challenging task especially when factors such as airplane delays, passenger check-ins, luggage inspections and passenger wait time policies are considered. This paper discusses a simulation model of passenger check-ins and security checkpoints at the Calgary International Airport using SimFC. A simple case study of US bound passengers from Calgary is presented. Based on passenger throughput levels and traffic intensity, airport-level human resource allocation recommendations for the number of check-in agents and passenger facing security personnel are made. The findings are of particular interest to researchers and industry professionals involved in airport service planning and management.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".