ARAS-FUCOM approach for VPAF fighter aircraft selection
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
Multi-criteria decision making (MCDM) methods are systematical science projects to help decision-makers reach accurate decisions. Applying MCDM methods in the military is important because accurate decision making is the deciding factor for success and can reduce expenditure and increase defense capability. The full consistency method (FUCOM), one of the methods in the MCDM group, has many advantages, and its results are reliable. This paper aims to evaluate and select an appropriate fighter aircraft for Vietnam People’s Air Force. Using FUCOM as a decision-making process, we find the final weight values of criteria and apply the additive ratio assessment (ARAS) method to derive the final ranking of alternatives to comply with criteria. Sensitivity analysis is conducted and the result is compared with the weighted product method to substantiate the sturdiness of the proposed method. The results show the Su-35 as the best available solution.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it