Multicriteria Spatial Decision Analysis for the Development of the Italian Minor Airport System
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
The infrastructures supporting air transport throughout the world in the civil sector are classified as primary-level (large numbers of passengers and goods on both commercial and charter long- and medium-haul flights) and secondary-level (few passengers and goods on general aviation private, short-haul flights). In parallel with primary-level air traffic general growth all over the world and in Italy, the popularity of “individual” nonscheduled general aviation traffic increased in many countries since 1990s. The latter aviation has proved to be a valid alternative to rail and road transport for short-medium distance journeys (100-500 km) for classes of business and tourist passengers. In keeping with the national and international airport system development scenarios, the paper illustrates the results of in-depth analyses aiming to construct an integrated GIS-based Multicriteria Decision Analysis evaluation methodology. It gears towards formulating strategies for the development and streamlining of some existing (51) Italian minor airports and for the right locations for the new hubs required to construct an efficient second-level air transport network (the “highway in the sky”). Different levels of evaluation verify the suitability of airport services and infrastructure (status quo) and the attractiveness of airport hubs given the territorial facilities found in their catchment areas.
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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 | 0.000 |
| 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 it