Comparison of measured and computationally simulated Mean Radiant Temperature. Case study of Campo de Ourique quarter in Lisbon
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mean Radiant Temperature (MRT) is one of the most relevant human bioclimatic indices, particularly suitable for assessing the influence of climatic parameters on thermal comfort outdoors. MRT can be calculated either based on physical measurements, carried out using a pyranometer and a pyrgeometer for quantifying short and long wave radiation fluxes, either by computational simulation. The first method is accurate, however it requires the measurement of radiant fluxes from six directions, is time consuming, complex, and it also requires expensive equipment. The second method is based on using the RayMan, ENVI-met and SOLWEIG computational models often employed in urban climatological research. The present research deals with the comparison of MRT data obtained by measurement and computational simulation for a dense city quarter of Lisbon: Campo de Ourique. The measurements were carried out during four summer days in 2006, in a park and in the surrounding canyon streets. An overall good fit can be observed between the simulated and the measured MRT values, however significant punctual differences can occur.
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.
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 | 0.000 | 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) | 0.000 | 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 it