Bibliographic record
Abstract
Wind plays always an important role in dealing with outdoor human comfort in an urban climate. Although various models of different complexity have been proposed to characterize the effect of wind on pedestrians in relation to their specific activities, it has been also recognized that human comfort in general may be affected by a wide range of additional parameters, including air temperature, relative humidity, solar radiation, air quality, clothing level, age, gender etc. Several criteria have been developed in the wind engineering community for evaluating only the wind-induced mechanical forces on the human body and the resulting pedestrian comfort and safety. It is also noteworthy that there are significant differences among the criteria used by various countries and institutions to establish threshold values for tolerable or unacceptable wind conditions even if a single parameter, such as the wind speed is used as criterion. These differences range from the speed averaging period (mean or gust) and its probability of exceedance (frequency of occurrence) to the methodology of evaluation of its magnitude (experimental or computational). The paper attempts to review some of the work carried out in this area and to address some of the most recent efforts to develop wind ordinances, as well as to incorporate additional parameters in order to specify the threshold values or comfort ranges for respective weather parameters. Ideally, for design purposes, an approach towards the establishment of an overall comfort index taking into account wind conditions and other microclimatic factors should be an ultimate objective. Contact person: T. Stathopoulos, Professor and Associate Dean, 1515 St. Catherine W., Room EV-6.125, 514-848-2424 ext. 3186 and 514-848-7965 (FAX). E-mail statho@bcee.concordia.ca Wind and Comfort
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.003 |
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".