Energy Efficient Ventilation for Maintaining Indoor Air Quality in Large Buildings
Bibliographic record
Abstract
this paper was presented at the 3rd International Conference on Cold Climate Heating, Ventilating and Air-conditioning, Sapporo, Japan, November 2000 C. Y. Shaw Rsum Institute for Research in Construction, National Research Council Canada Achieving good indoor air quality in large residential and commercial buildings continues to be a top priority for owners, designers, building managers and occupants alike. Large buildings present a greater challenge in this regard than do smaller buildings and houses. The challenge is greater today because there are many new materials, furnishings, products and processes used in these buildings that are potential sources of air contaminants. There are three strategies for achieving acceptable indoor air quality: ventilation (dilution), source control and air cleaning/filtration. Of the three, the most frequently used strategy, and in most cases the only one available to building operators, is ventilation. Ventilation is the process of supplying outdoor air to an enclosed space and removing stale air from this space. It can control the indoor air quality by both diluting the indoor air with less contaminated outdoor air and removing the indoor contaminants with the exhaust air. Ventilation costs money because the outdoor air needs to be heated in winter and cooled in summer. To conserve energy, care must be taken to maximize the efficiency of the ventilation system. In this regard, a number of factors come into play
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.001 | 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 teacher head, 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".