Simulation based assessment on representativeness of a new performance rating procedure for cold climate air source heat pumps
Bibliographic record
Abstract
Cold climate air-to-air heat pumps (CCHP) offer a strong potential for energy use reductions in Canadian homes. Proper selection of the unit is critical in order to take advantage of the improved efficiency and increased heat capacity at low ambient temperatures and ability to modulate to meet a wide range of heating loads. A new performance rating procedure (CSA EXP07) was developed to better represent the seasonal energy efficiency of CCHP systems versus current test procedures that do not always accurately characterize the response to dynamic loads in a colder climate zones, thus resulting in inaccurate equipment rating. To validate the representativeness of the new performance rating procedure and quantify the potential over-or underestimation of energy savings using current performance rating procedures, a CCHP data-driven model is developed and simulated in a code-compliant single-detached Canadian home for different climate regions: Marine, Cold-Humid, Cold-Dry, Very-Cold and Subarctic. These energy models then serve as the basis for comparing the seasonal heating coefficient of performance of a CCHP system, which can be compared to the current and newly proposed performance rating procedure.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".