Balancing Trade-offs between Deep Energy Retrofits and Heritage Conservation: A Methodology and Case Study
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
Drastic reductions in energy consumption within existing buildings are required to achieve climate change mitigation targets. However, a portion of existing buildings have important historic values that need to be conserved. The goal of this paper is to present a methodology and decision-framework for deep energy retrofit analyses that balances trade-offs between conservation and sustainability. This methodology includes historic recording, documentation, a detailed energy model, and calibration to monthly data. An historic house in Ottawa, Canada is studied to demonstrate the use of the methodology. The energy retrofit analysis suggests 67% energy savings are achievable by increasing envelope thermal resistance to 4.1 m2-K/W, reducing air infiltration by 70% to 4.2 ACH at 50 Pa through air sealing and an air-vapour barrier, rehabilitating windows to be triple-pane low-E assemblies, using an air-source heat pump to supplement the existing gas boiler, daylight sensors and controls, and solar PV panels.
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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 | 0.000 | 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 it