Proceedings of the 6th ACES Symposium, May 11–16, 2008, Cairns, Australia: Introduction to the Special Issue
Bibliographic record
Abstract
The APEC Cooperation for Earthquake Simulations (ACES) held its 6th general symposium in Cairns, Australia from May 11-16, 2008.On the second day of the symposium, the importance of the ACES organization was underscored by the occurrence of the May 12, 2008 Wenchuan, China earthquake that killed more than 80 000 persons near the major metropolis of Chengdu, China.The 7th general symposium is to be held at Otaru, Japan during October 3-8, 2010, hosted by the government of Japan.The ACES organization was authorized by the Industrial Science and Technology Working Group of APEC at the 1997 Singapore meeting, in response to a resolution introduced by the government of Australia.As stated on the ACES home page, http://quakes.earth.uq.edu.au,earthquakes are one of the most costly and deadly natural disasters.APEC member economies are struck by the vast majority of the world's earthquakes and have a particularly high earthquake risk.This has resulted in more than 800 000 deaths in APEC member economies of the approximately 1.3 million deaths associated with earthquakes during the 20th century.During the 21st century, approximately 750 000 deaths have so far occurred as a result of earthquakes in India, Sumatra, Pakistan, China, and Haiti.The scientific method relies on the development of a theoretical framework or simulation model describing nature.While no such model exists for the complete earthquake generation process, conceptual developments in understanding earthquake physics, numerical simulation methodology and advances in High Performance Computing offer the possibility to develop such models.The APEC Cooperation for Earthquake Simulation (ACES) has capitalized on this opportunity and the complementary strengths of the earthquake research programs of individual APEC member economies.The ACES collaboration aims to develop numerical simulation models for the complete earthquake generation process, to assimilate new earthquake observations into such models, to foster collaboration between the relevant programs of participating member economies, and to foster the development of the required research infrastructure and research programs.Ultimately it is expected that these models will lead to progress in the difficult task of earthquake prediction and forecasting.Development of such simulation models represents a grand scientific challenge because of the complexity of phenomena and the range of scales involved from microscopic to global.These models are providing powerful new tools for studying earthquake precursory phenomena and the earthquake cycle.They have direct application to earthquake hazard studies and earthquake engineering, and the potential to yield spin-offs in sectors such as mining, geophysical exploration, high performance computing, material sciences, engineering and geotechnical studies.Seven Science Working Groups (WGs) have been established with five relating to construction of physically based numerical simulation models for the earthquake generation process and the
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.188 | 0.084 |
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".