Integration of MACBETH and COPRAS methods to select air compressor for a textile company
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
The selection of air compressor is a Multiple Criteria Decision Making (MCDM) problem including conflicting criteria and various alternatives. Selecting the appropriate air compressor is an important decision for the company as it affects the energy consumption and operating cost. To aid the decision making process in the companies, MCDM methods are proposed in the literature. In all MCDM methods, the main goal is to select the best alternative or to rank a set of given alternatives. In this paper, the air compressor is selected for a spinning mill of a textile company with an integrated approach based on MACBETH (Measuring Attractiveness by a Categorical Based Evaluation TecHnique) and COPRAS (COmplex PRoportional ASsessment) methods. MACBETH method is utilized to determine the weights of the criteria. Then COPRAS method is used to determine the ranking of the alternatives and select the best one.
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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 | 0.017 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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