A New Calculating Model for the Suitable Area of Air Cleaners Purifying Indoor Gaseous Chemical Contaminants
Bibliographic record
Abstract
Suitable area is an important index when selecting air cleaners. The suitable area's models in corresponding standards in American, Canada and Japan are all set up according to the particulate matters concentration equation. The suitable area can be calculated by multiplying a coefficient with CADR. However, air cleaners are also used to remove indoor gaseous chemical contaminants. The suitable area for particulate matters may not be reasonable for gaseous chemical contaminants. A new model to calculate the suitable area for indoor gaseous chemical contaminants has been set up. Using the CADRs of six tested air cleaners on the market, we compared the suitable areas of the air cleaners in different contaminant concentration levels. The results show suitable areas for gaseous chemical contaminants are much smaller than those for particulate matters. It is of great importance to distinguish suitable areas for different contaminants and the new model has a great reference value.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".