Analysis of gravity disturbance data for the detection of crustal-scale structures: insights from central Italy and surrounding regions
Bibliographic record
Abstract
North-central Italy is cored by the Apennines mountains, which are the product of Cenozoic convergence between the Adriatic microplate and the European plate. The Apennines display complex lateral variations in surface geology, some of which could be associated with a postulated yet controversial tear in the subducting Adriatic lithosphere. This research uses spectrally filtered World Gravity Model (WGM) 2012 gravity disturbance data to highlight linear changes in the data at different inferred depths, interpreted as proxies for location of crustal-scale geological structures. Gravity “worms” (multiscale wavelet edges of the gravity disturbance data) are used to supplement lineament interpretation and emphasize structural contacts. Results show that while the lineament characteristics vary at three different depth intervals (~2-25 km, ~25-50 km, and >50 km), certain major lineaments are continuously expressed. The study area is additionally subdivided into five major domains corresponding to different dominant orientations of the gravity lineaments. The lineament patterns within the domains likely highlight major structures in regions that experienced contrasting tectonic evolutions leading up to the present-day configuration. Furthermore, the gravity lineaments at all three inferred depth slices tend to show a spatial correlation with major lithological boundaries. Gravity lineaments at the shallow depth slice spatially correlate with surficial features such as the edges of Neogene-Quaternary sedimentary basins, topographic ridges in the surrounding Tyrrhenian, Ligurian, and Adriatic seas, as well as geomorphological features in the Northern Apennines. The lineaments in the shallow and intermediate depth slices tend to align with major thrust faults across the study area, as well as with transverse lineaments that have been well-documented in the northern Apennines. The lineaments in the deepest slice appear to align with seismicity patterns. Finally, a set of gravity lineaments, imaged across all three depth slices, is consistent with the location of the postulated subduction tear in the Northern Apennines, thereby supporting this hypothesis. Our results suggest that analysis of lineament patterns from gravity disturbance data is a powerful tool to detect lithospheric-scale structures and identify domains that can provide insight into the tectonic evolution of a complex area.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".