Insights and Reflections: The 'Exploring Unprecedented Extremes' Workshop
Bibliographic record
Abstract
Due to the various regions and contexts around the world with distinct climatic characteristics, climate hazards vary significantly in their nature, frequency, and impact, causing property damage, population distress, communication failures, environmental damage, and economic losses. Unfortunately, 2023 showcased extreme weather and climate events that have surpassed previous records. These include heatwaves, floods, wildfires, tornadoes. The occurrence of these extreme events poses a challenge to our comprehension of future climates, primarily due to their divergence from our conventional thought patterns or their status as out-of-sample scenarios. With ongoing climate warming, the potential for more severe events in the future is a concern. Insufficient preparation may result in breakdowns within specific sectors or even societal collapse. Effective preparation involves multiple factors, with the initial challenge lying in forming expectations - a task complicated by events that fall outside our usual anticipations, such as out-of-sample occurrences. In the face of those climate challenges, understanding and mitigating the impacts of unprecedented climate extremes has become a critical area of focus. To shed light on this challenge, a workshop titled "Exploring Unprecedented Extremes" was convened in November 2023. This event brought together experts from diverse fields to deliberate on innovative approaches to climate change adaptation and mitigation. Emphasizing co-creation and interdisciplinary collaboration, the workshop addressed key themes such as the integration of various sectors into climate change strategies, the complexities of decision-making under uncertainty, and the crucial role of transdisciplinary research in comprehensively understanding and effectively responding to climate extremes. This poster focuses on the key takeaways and strategic reflections that emerged following the workshop, capturing the essence of our collaborative discourse on climate challenges.
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 | 0.026 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.019 | 0.012 |
| Open science | 0.006 | 0.022 |
| Research integrity | 0.016 | 0.041 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".