Reflections on the Evidentiary Basis of Indoor Air Quality Standards
Bibliographic record
Abstract
Buildings are expected to provide healthy and comfortable indoor environmental conditions for their users. Such conditions have diverse dimensions, including thermal, visual, air quality, auditory, and olfactory aspects. Indoor environmental quality standards, guidelines, and codes typically inform professionals in the building design and operation phase in view of procedural, contractual, and legal boundary conditions. Given this critical role of standards, it seems significant to examine the applicability and scientific validity on a regular basis. In this context, the present paper focuses on the standard-based definition of indoor air quality (IAQ) indicators and their respective values. Hence, the main aim of this effort is to study several common national and international IAQ standards in view of the scope to which they include direct or indirect evidence for the validity and applicability of their mandates and requirements. To this end, selected IAQ standards were assessed via a structured schema that includes not only basic information, quality indicators, and suggested and recommended value ranges, but also any reference to scientific studies. The findings of this effort identify certain issues with the transparency of the chain of evidence from the results of technical literature and standard-based IAQ recommendations. Moreover, recommendations are made for the development of future transparent and evidence-based IAQ standards and guidelines.
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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 | 0.211 | 0.227 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.005 | 0.049 |
| Scholarly communication | 0.020 | 0.022 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.009 | 0.019 |
| Insufficient payload (model declined to judge) | 0.002 | 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".