Comparison of measured and computationally simulated Mean Radiant Temperature. Case study of Campo de Ourique quarter in Lisbon
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.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".