Magnetogravimetric study on the Scotia Plate, in the South Atlantic Ocean for the characterization of tsunamis
Bibliographic record
Abstract
The marine and coastal environments of the Scotia Sea regions in the Southern Atlantic Ocean and Antarctica are vulnerable to the potentially disastrous effects of seismic activity along the Scotia Arc. This paper presents a magnetogravimetric study of the Scotia Plate for tsunami characterization. The influence of earthquakes on the Geomagnetic Field (GMF) is investigated using data from INTERMAGNET network observatories. A tectonic model is evaluated using gravity data from NOAA and seismic refraction data from Lamont-Doherty Earth Observatory. The study also assesses the impact on water level (WL) measured at Intergovernmental Oceanographic Commission (IOC) tide gauge stations. Cross Wavelet Transform (XWT) is applied, and a frequency analysis of the GMF is conducted to identify specific frequencies during seismic events. A 2D tectonic model is constructed for the North Scotia Ridge using gravimetric and seismic data to characterize structural boundaries that may be activated during seismic events. Water level records collected from 6 tide gauge stations in the region are filtered and analyzed to identify tsunamis at each station. The results reveal anomalous frequencies in the frequency analysis of the horizontal component of the GMF during the November 25, 2013 earthquake, with high data correlation from different observatories in the study area for periods of 0.5 and 1 hour. Gravimetric modeling delineates faults activated during seismic activity and edges of structures potentially activated due to the transcurrent and compressional nature of the margin. WL anomalies up to 1.30 m are obtained following earthquakes with a magnitude greater than 8. The propagation speed in the study area averaged 460 km/h, consistent with the expected speed for those depths, except for Puerto Argentino, which exceeded them in 50%.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".