Weighted Aggregated Sum Product Assessment
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
Multiple Criteria decision-making (MCDM) approaches are required for complex issue resolution. However, it is debatable whether MCDMs applicability will be able to stay within the analytical possibilities for dealing with divorce issues. As a result, one of the newly introduced MCDMs Weighted aggregated sum product assessment (WASPAS), is chosen for evaluation. Therefore, this study examined 388 documents from archive of the Scopus database. To evaluate the diversity of the technique's application, the data analysis looked at a few bibliometrics measures. So, the publishing hosts and their influence patterns are displayed, the vast majority of the documents were in the fields of engineering and computer science. According to the findings, the WASPAS can deal with variety of problem-solving scenarios. Hence, this work is summed up with the aim of lowering uncertainty among decision-makers and scholars.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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