Bibliographic record
Abstract
The PMV index forms the basis of international thermal comfort standards. PMV was developed based on empirical relationships between the metabolic rate of activity and the body mean skin temperature and evaporative heat loss under the comfort conditions. However, many recent studies have questioned the accuracy and reliability of the PMV predictions, particularly for the discomfort range. This paper develops a general formulation of PMV that does not involve the mean skin temperature and evaporative heat loss. The new metabolic-based predicted mean vote (MPMV) index is expressed as the difference between the metabolic rate of activity and the metabolic rate required to achieve a comfort state under the imposed environment conditions. The comfort metabolic rate is found to vary linearly with the metabolic rate required to maintain the body core and mean skin temperatures at the resting thermo-neutral state. The model constants are determined using public experimental data on thermal sensation votes of young and older people. The new formulation accounts for body core cooling to achieve comfort under hot exposures; it also addresses the overlooked non-shivering thermogenesis in the body heat balance at the comfort state and covers comfort requirements for young and older people in wakeful and sleep states.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".