A database of house descriptions representative of the Canadian housing stock for coupling to building energy performance simulation
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
The development of a simulation tool that can accurately characterize the energy performance of the Canadian housing stock would enable detailed studies to predict the impact of energy saving upgrades and technologies on a national scale. Such a tool requires a detailed database of house descriptions that collectively represent the entire housing stock. Such a database has been assembled by selectively extracting measured and observed data collected by professionals who conducted on-site audits of 200,000 houses. The auditors' data were extracted to statistically match key parameters (location, house type, vintage, geometry and heating system) with a broad-based random survey of the Canadian stock. The result is a database comprised of nearly 17,000 detailed records of single-detached, double and row houses. Each of these house records represents ∼500 houses in the Canadian stock and contains sufficient data to enable the accurate characterization of its energy performance through building performance simulation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 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 it