Mitigating the negative impact of new buildings on existing buildings’ user comfort—a case study analysis
Bibliographic record
Abstract
Campus master plans are released every few years for developing and implementing its physical infrastructure. Open spaces, compactness, connectivity, greenness, and environmental impact have often been the focus on its framework. In particular, the effect of new building development on existing buildings' occupant comfort and design intent is mostly ignored. Providing guidelines to retain existing users' comfort for stakeholders involved in design decision making will result in improved design decisions. Hence, this research aims to provide a work methodology to mitigate the adverse effects of new buildings on existing buildings' user comfort through a case study at Carleton University. The case study shows a methodology to retain the existing users' comfort by analyzing Carleton University's master plan on massing studies, occupant survey to understand their comfort needs, performance analysis of the impact of the new building on the existing building user comfort. The analysis reveals the key parameters to consider in design for occupants' comfort. Finally, the research reinforces the generative design and the need for dynamic modeling in campus master plans to mitigate the negative implications of new development on occupants' comfort.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".