Evaluating and Improving the Energy Performance of School Buildings with a Proposed Real-Time Monitoring System
Bibliographic record
Abstract
Building energy consumption occupies a significant portion of the final energy consumption, and its trend is increasing. Due to a substantial contribution to the energy use of commercial sector by office buildings, much attention has been brought to them with energy-efficient measures. However, there are only a limited number of studies investigating the school building's energy consumption performance, especially in Canadian cold climate, which it allows opportunities for improving school building's energy efficiency. In this study, the historical electricity consumption and energy-related costs of Edmonton Catholic Schools are statistically analyzed. Energy benchmarking methods are applied to evaluate the energy performance of schools and categorize them. With the aim of improving the energy performance of school buildings by discovering energy saving opportunities existed in them, an electrical management program is proposed with the real-time monitoring system. The proposed framework for lowering the electricity consumption of schools can be continually used by school facility operators in the future to identify inefficient school buildings and electricity abusers inside them.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".