A dataset from a coordinated multi-site laboratory study investigating the Hue-Heat-Hypothesis
Bibliographic record
Abstract
Understanding cross-modal environmental perception is essential for improving occupant well-being and human-centric building design. This paper presents an open-access, multi-site database developed under the IEA-EBC Annex 79 project to test the Hue-Heat Hypothesis (HHH), which hypothesizes that light hue may influence thermal perceptions. The database comprises 543 experimental rounds conducted in eight laboratories across six countries and diverse climate zones, following a shared, rigorously designed protocol. During summer and winter campaigns, participants were exposed to controlled thermal environments and counterbalanced lighting conditions (neutral, reddish, bluish). The database includes detailed metadata on environmental variables, physiological measurements (i.e., heart rate and skin temperature), and self-reported perceptual responses. It also provides standardized technical documentation for each test room, including the detailed experimental protocol and translated survey instruments. All materials are available on the Open Science Framework under the "Multi-site Hue-Heat-Hypothesis Testing" repository. This resource supports research into multi-domain human comfort, enabling analysis of cross-modal and combined effects on human perception and physiological reactions.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".