Bibliographic record
Abstract
Window air conditioners are the dominant cooling product for residences, in terms of annual unit sales. They are inexpensive, portable and can be installed by the owner. For this reason, they are an attractive solution for supplemental cooling, for retrofitting air conditioning into a home which lacks ductwork, and for renters. Window air conditioners for sale in the United States are required to meet very modest minimum efficiency standards. Four window air conditioners' performance were tested in the Advanced HVAC Systems Laboratory on NREL's campus in Golden, CO. In order to separate and study the refrigerant system's performance, the unit's internal leakage pathways, the unit's fanforced ventilation, and the leakage around the unit resulting from installation in a window, a series of tests were devised that focused on each aspect of the unit's performance. These tests were designed to develop a detailed performance map to determine whole-house performance in different climates. Even though the test regimen deviated thoroughly from the industry-standard ratings test, the results permit simple calculation of an estimated rating for both capacity and efficiency that would result from a standard ratings test. Using this calculation method, it was found that the three new air conditioners' measured performancemore » was consistent with their ratings. This method also permits calculation of equivalent SEER for the test articles. Performance datasets were developed across a broad range of indoor and outdoor operating conditions, and used them to generate performance maps.« less
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.973 | 0.979 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".