The Integrated Combined Compromise Solution Method and Distance-Based MCDM Model with Application
Why this work is in the frame
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Bibliographic record
Abstract
This research compares the Combined Compromise Solution MCDM Method with some other known Multi-Criteria Decision-Making methods. We also propose an improved form with a new integration function based on a nonlinear optimization programming model with maximum kurtosis to the existing model. We also extend Ye and Li's fuzzy distance base model to include the centered possibilistic variance as one of the essential elements in calculating the relative closeness coefficient for alternatives in the decision-making process. The possibilistic model proposed by Ye and Li deviates in principle from the theory of possibility theory as formulated by Carlsson and Fuller. Towards the end of the paper, we discuss an approach to select the best Covid Vaccine within a pool of various other competitive, equally efficient vaccines.
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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