New Class of M-Polar Fuzzy Measure Ideals Algebra in BCK2/BCK1/BCI2
Bibliographic record
Abstract
In this work, we introduced the concepts of fuzzy measure algebra of the M-polar electrode ambiguous ideals, and many of them have been investigated properties. Characterizations of the blurry M-polar measure sub-algebra and fuzzy (commutative) ideals of polarity are also looked at. Also, the relationships between M-polar fuzzy measure subalgebras, and M-polar ambiguous and ambiguous pole reciprocal ideals have been discussed. A new Concepts suggested here can be expanded to different types of ideals in BCK2, BCK1 and BCI2-algebras, for instance, a-ideal, implicated, n-fold and n-fold ideals, and commutative ideals. Besides, the properties of BCK2 (resp, BCK1 and BCI2) M-polar fuzzy measure algebra are discussed. Finally, the study also investigates the relationships between the mysterious BCK2 (resp, BCK1 and BCI2) M-polar fuzzy measure ideal. Some examples related to it are also given.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".