THERMAL AND MECHANICAL SYSTEMS DESCRIPTORS FOR SIMPLIFIED ENERGY USE EVALUATION OF CANADIAN HOUSES
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
For a quick and reliable energy evaluation of houses, one needs simple energy analysis software. A key requirement for simplified inputs is to have default data for house geometry, thermal and equipment characteristics based on vintage, type and region in which the house is located. Using data collected from more than 634,000 homes, statistical representative archetype data sets were developed for 35 climates zones and eight vintage periods. Representative numerical approaches were applied to develop archetype house characteristics. These data libraries are integrated with energy simulation software to assist in defining required defaults for geometry, building envelope and equipment. These defaults then provide guidance for a energy advisor to check against actual house data. Comparative energy analyses showed that the archetype characteristics are useful in quick field surveys.
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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