Hybrid Multi-attribute Decision Making Method of Electric Coal Procurement in Industry
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
Electric coal procurement is the basis of electric power production. In this paper, the problem of supplier selection is studied in multi-source procurement of electric coal. Concretely, the index system of supplier selection is presented, including the evaluation attributes of price, quantity, quality, delivery time and the reputation of supplier. Then, the problem of supplier selection is converted into a problem of hybrid multi-attribute decision making, and a projection method based on hybrid technique for order preference by similarity to ideal solution (TOPSIS) is presented to rank all suppliers and select winners. Its decision example is also given to implement the presented decision method and to demonstrate its effectiveness and practicality. This paper gives an effective way to the hybrid multi-attribute decision making for multi-source procurement of electric coal under fuzzy uncertain environment.
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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 | 0.006 |
| 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 | 0.000 | 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