Meet the AMS Board on Urban Environment
Bibliographic record
Abstract
The American Meteorological Society’s (AMS) Board on the Urban Environment (BUE) serves as a dynamic platform for the urban climate community, fostering collaboration and innovation in urban meteorology and related fields. The BUE addresses a broad spectrum of topics, including urban land-atmosphere interactions, urban heat island effects and mitigation, urban biometeorology, urban air quality, urban circulation and mesoscale impacts, and global change impacts on cities. The BUE plays a pivotal role in uniting researchers, practitioners, and policymakers by organizing symposia, webinars, and outreach initiatives that stimulate discussion and promote cutting-edge research. Through these efforts, the Board provides a focal point for the urban climate community and raises awareness of critical challenges and opportunities in urban meteorology. It also supports the publication of high-quality research and recognizes excellence through awards such as the prestigious Helmut E. Landsberg Award. Structured leadership and diverse committees ensure the Board’s effectiveness, but in particular, student representatives bring fresh perspectives and bridge early-career researchers with experienced professionals. The BUE is committed to advancing scientific knowledge, encouraging collaboration, and addressing the pressing challenges of urban environments. By connecting individuals and organizations across the urban climate community, the Board inspires impactful research and practical solutions for cities worldwide. Join us in shaping the future of urban meteorology and addressing the critical issues facing our rapidly urbanizing world!
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.201 | 0.109 |
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".