Lithospheric Structure of Africa and Surrounding Regions Revealed by Earthquake and Ambient Noise Surface Wave Tomography
Bibliographic record
Abstract
To advance the understanding of the tectonic processes shaping the African continent, we construct the first continental-scale shear-wave velocity (Vs) model of the crust and uppermost mantle from joint analysis of ambient seismic noise and earthquake data recorded by ~1529 broadband seismic stations located in Africa, Arabia, and Europe from 1987 to 2018. We apply the widely used ambient noise cross-correlation and earthquake two-station methods to retrieve the fundamental-mode Rayleigh-wave group and phase velocity dispersions in the period range of 5 – 50 s which are jointly inverted using the neighbourhood algorithm to build a new three-dimensional Vs model with associated uncertainties. The inclusion of relatively short-period dispersion data from ambient seismic noise allows us to achieve better resolution at shallow depth and obtain a more accurate model than previous global and continental-scale studies, revealing lithospheric structures that correlate well with known tectonic features. In sparsely instrumented regions of north-central Africa, our model provides seismic evidence for the existence of cratonic remnants beneath thick sediments within the poorly imaged Sahara Metacraton and reveals unique mantle upwelling beneath hotspots, suggesting that they may be fed by unconnected plumes. The estimated crustal thickness varies among and within tectonic provinces and shows no clear evidence for the secular variation in crustal genesis. Our new model has the potential to serve as a preliminary reference velocity model for Africa and is useful for practical applications, including monitoring of the Comprehensive Nuclear-Test-Ban Treaty, geodynamic modeling as well as seismic hazard analysis.
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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 | 0.001 | 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) | 0.000 | 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".