Interval-Valued Intuitionistic Fuzzy Yager Power Operators and Possibility Degree-Based Group Decision-Making Model
Why this work is in the frame
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Bibliographic record
Abstract
Abstract As an extended form of intuitionistic fuzzy set, the theory of interval-valued intuitionistic fuzzy set (IVIFS) can describe fuzziness more flexibly. This study aims to develop a group decision-making model based on the distance measure, Yager power aggregation operators and the possibility measure in the context of IVIFSs. For this purpose, new distance measure is proposed to quantify the dissimilarity between two IVIFSs. In addition, comparison with existing distance measures is performed to illustrate the efficiency of introduced measure. Combining the Yager’s triangular norms with the proposed distance-based power operators, a series of interval-valued intuitionistic fuzzy (IVIF) Yager power aggregation operators are introduced with their desirable properties. Moreover, a possibility measure is developed for pairwise comparisons of IVIFSs, which overcomes the shortcomings of existing IVIF-score function, IVIF-accuracy function, and IVIF-possibility measures. The developed possibility measure is further utilized to compute the weights of criteria. To prove the practicality and effectiveness of introduced model, it is applied to a case study of manufacturing plant location selection problem with IVIF information. Finally, sensitivity and comparative analyses are carried out to test the stability and robustness of the proposed method under the setting of IVIFSs.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| 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