Green Worship House Competition as an Effective Tool to Evaluate Green Pyramid Rating System (GPRS)
Bibliographic record
Abstract
Egypt is divided into seven regional units; each region includes a number of governorates that are connected geographically and economically. When the Green Pyramid Rating System (GPRS) was proposed, and the weightings of its categories were set, the wide variation of the potential and the challenges of each region were not taken into account. Therefore, the study focused on highlighting these differences, and the main focus on Sinai region by analyzing the experience of activating The Green Pyramid Rating System (GPRS) during a competition held for this purpose. Accordingly, this paper presents an investigation into the international GBRSs to extract the specifications of a framework to improve GPRS classification, based on the experience of activating GPRS principles in Green Worship House Competition (GWHC) and the observations of participants of the competition. The study included a summary of what was suggested during participation in the competition to activate each category of Green Pyramid Rating System (GPRS), in addition to observations and problems encountered in the design of the project and activation of (GPRS) categories, then suggestions for developing the categories and weights of each category based on active participation in the Green Worship House Competition.
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How this classification was reachedexpand
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 | 0.005 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".