Three-Way Multiattribute Decision-Making Based on Outranking Relations
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
In contrast to two-way decisions (2WD), three-way decisions (3WD) can effectively reduce decision risks by utilizing a new delayed decision option. This article incorporates 3WD into multiattribute decision-making (MADM) based on an outranking relation. We construct the outranked set for each alternative and introduce a hybrid information table that combines an MADM matrix with a loss function table. We propose three strategies to design a new 3WD model for MADM. The rationality and effectiveness of the proposed 3WD method are demonstrated by solving a problem of enterprise project investment target selections. Finally, we provide the comparative analysis and two experimental evaluations. The results show that the proposed 3WD method is effective and practically useful.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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