Assessment of the level of service (LOS) of public recreational centre buildings : an uncertainty based approach
Bibliographic record
Abstract
The federal sustainable development strategy (FSDS) for Canada advocated that public sector operations should aim at shrinking the environmental footprint while enhancing social benefits. In this quest, improving the sustainability performance of public buildings becomes a key constituent since buildings are responsible for the highest portion of the corporate GHG emission and energy usage of public entities. Moreover, public buildings are an important constituent of the socio-economic environment of a local region. Hence, there is a need for improving the sustainability performance of the future and existing public buildings. Currently, various innovative methods are used by federal, provincial and municipal entities to improve the sustainability performance of public buildings. However, asset management of building has been overlooked from the above studies. There is a lack of comprehensive methods to assess the level of service (LOS) of a building that is crucial for life cycle asset management. To address this problem, this paper proposes an approach to calculate the LOS of a recreational centre building operated by municipal government. Firstly, a LOS framework is formulated for recreational centre building by taking into consideration the key aspects. Secondly, a fuzzy synthetic evaluation method is used to assess the building performance. Thirdly, a case study was conducted to validate the proposed methodology. Results from this approach provide detailed information about the performance of the building assets. This approach facilitates in identifying areas that require immediate attention for improvement. This study provides a novel approach to life cycle asset management of public sector buildings.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".