Progress in GTEWS Ground Displacement Measurements and Tsunami Warning
Bibliographic record
Abstract
Abstract Since its early days, GNSS has been employed for the monitoring of sudden ground movements, such as earthquakes. Its use as a tool to enhance tsunami detection was boosted after analysis of data following the December 2004 Great Ocean Indian Tsunami. The contribution of GNSS towards tsunami warning systems is possible due to several factors, such as advances in the measurement of crustal displacement, developments in GNSS methodology, the growing availability of real-time data streams and advances in processing power and communication means. The paper focuses on the progress of Global Navigation Satellite System Tsunami Early Warning Systems (GTEWS) identifying current implementations and future directions and challenges. The discussion leads to the conclusion that the GNSS technology already satisfies requirements of tsunami early warning systems and that the major hurdles are with other aspects, such as optimal network configuration, real-time flow of data, communication infrastructure, and national and international collaboration. The paper ends highlighting the important role that the Global Geodetic Observing System (GGOS) can play to help overcoming those hurdles.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".