Insights into Seismogenetic Areas in Central Italy from Combined Absolute Gravity and GNSS Measurements
Bibliographic record
Abstract
In this study we present and discuss gravity and ground deformation variations, at different time scales, observed in a wide mesh absolute gravity and GNSS network set up in central Italy. The network was installed in the area affected by the 2009 (L’Aquila; Mw 6.1) and 2016 (Amatrice-Norcia; Mw 6.0 and 6.5) seismic activity, in order to verify if gravity and ground deformation variations could be related to seismic effects. The new network includes 5 stations distributed between the Lazio, Umbria, and Abruzzo regions. From 2018 to 2020 three campaigns were carried out using the transportable Micro-g LaCoste FG5#238 and the portable Micro-g LaCoste A10#39 absolute gravimeters and completed with two simultaneous GNSS measurements. Topographic instruments, measurement and analysis techniques enabling accurate measurements in the positioning of the stations and to control their variations over time were applied. The high reliability and accuracy of the absolute gravity data gathered, after being corrected for known effects, showed a negative short-term (2018–2020) pattern throughout the area, up to −30 µGal. Since some stations of the new network coincided with benchmarks already measured in the past, an analysis of long-term gravity changes was carried out and a fair degree of stability was observed in two stations, while positive large variations, of approximately 70 and 157 µGal, were recorded in the other two stations in the time intervals 1954–2020 and 2005–2010, respectively. On the other hand, variations highlighted by GNSS height measurements were all below 3 cm. Here, the first long-lasting gravity measurements carried out with absolute gravimeters in a seismic area in Italy are presented, providing meaningful geophysical information. The obtained results, in terms of availability of a combined absolute gravity and GNSS network, definition of data acquisition and analysis procedures, as well as creation of a high quality data archive, lay the foundations for a multidisciplinary approach towards improving the knowledge of this seismogenetic area of Italy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".