Emergence Time Phasing for the Potential New Airports in the Middle District of Iraq
Bibliographic record
Abstract
With the growing demand for air transportation and limited capacity at Baghdad International airport (BIAP), there is a need to increase the capacity of airport systems in the middle district of Iraq. The increased use of secondary airports has been and is expected to be one of the key mechanisms by which future demand is met in congested metropolitan areas. This paper analyzed the factors influencing the emergence of secondary airports in the Iraqi middle district and the dynamics of multi-airport systems. A system dynamics model was developed to simulate the relationship between the core airport in Baghdad and three potential secondary airports, one in each adjacent governorate. The model takes under consideration such characteristics as; capacity, location, proximity to populated communities, and ground transportation services for each airport. the main outcomes of this model are; the passenger's persuasion in an airport, which reflects their propensity to use this particular airport, and the predicted number of annual passengers in each airport. The system dynamics model was consulted twice. The outcomes of the first run facilitated the economic analyses of the secondary airports on which the sequence of the airports emergence was determined, and it also showed that the new airport feasibility is highly affected by the location, due to the influence on the road user cost for passengers, in addition to the capital expenses. The second run of the model helped in predicting the time schedule and interval between an airport emergence and the other. If the new airports have an equal capacity of one million passenger per year, the expected timing for the emergence is in 2023, 2027, and 2032 for the airports in Balad, Habbaniyah, and Baquba respectively.
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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 | 0.001 | 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 | 0.000 |
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 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".