Understanding Applications and Best Practices of DEMATEL: A Method for Prioritizing Key Factors in Multi-Criteria Decision-Making
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
Decision Making Trial and Evaluation Laboratory (DEMATEL) method is a powerful tool for understanding and visualizing the causal relationships among factors in complex decision-making problems. The method uses diagrams and matrixes to map out the causal relationships and interdependencies among factors, allowing decision-makers to identify key drivers and potential solutions to the problem. DEMATEL has a wide range of application areas, including supply chain management, environmental planning, healthcare, finance, and engineering, among others. The DEMATEL method is a valuable tool for decision-makers who need to understand the complex causal relationships among factors in order to make informed decisions. The method provides a structured approach for analyzing and prioritizing factors and for identifying potential solutions to complex problems. This paper describes the main features of this method, its application areas as well as the main process steps in the DEMATEL method.
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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 | 0.043 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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