A new correlation measure of the intuitionistic fuzzy sets
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Bibliographic record
Abstract
In this paper, we regard the membership degree and the non-membership degree of the intuitionistic fuzzy set (IFS) as a whole and propose a new approach to measuring the correlation degree between the IFSs in finite sets. Like the computational process of the correlation coefficient between the real number variables, we first define the deviation of the intuitionistic fuzzy numbers, the variance of the IFS, and the covariance of the IFSs; then propose the formula to get the correlation coefficient between the IFSs. The proposed method not only reflects the symbol attribute of the correlation degree between the IFSs (the value of the correlation coefficient lies in the interval [–1, 1]), but also makes sure the integrity of the IFS is maintained. Several examples are given to show the feasibility and advantages of the proposed method. Moreover, we extend this approach to the interval-valued intuitionistic fuzzy set (IVIFS) case.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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