Seismicity and Surface Deformation in Kamanjab Inlier, Northern Namibia
Bibliographic record
Abstract
The last two decades have seen the onset of felt earthquakes, including occasionally damaging events, in the Kamanjab Inlier, a block of Paleoproterozoic crystalline basement in northern Namibia. The Geological Survey of Namibia (GSN) and the Council for Geoscience, South Africa (CGS) deployed a temporary network of 10 seismic stations within the Kamanjab Inlier from June to September 2018 and cataloged ~1500 events. We used a neural network-based earthquake phase detector, EQTransformer, to enhance the published GSN catalog to >9000 detections. The double-difference earthquake relocation of ~4500 events reveals two distinct major and three minor spatial clusters that we interpret as local discrete faults that intersect the NE-dipping seismogenic fault of the 4 April 2021 Mw 5.4 earthquake, which is the largest instrumentally recorded earthquake in Namibia to date. We name the Mw 5.4 host fault "Anker Fault" and constrain its orientation using Sentinel 1 Interferometric Satellite Aperture Radar (InSAR) to image surface uplift and subsidence patterns. Given the sudden onset of the 2018 seismic activity and the absence of dams, mineral or energy exploration projects nearby, we eliminated the possibility of anthropogenic triggering. We suggest that the proximal cause for 2018 seismicity is shallow groundwater migration, possibly associated with nearby hot springs and modulated by tidal forces. The Kamanjab Inlier area has shown an increase in the number and magnitude of earthquakes from 2018 to 2021, which could pose a seismic hazard in the future. Our study introduces an earthquake detection and relocation workflow that can be adopted for regions with limited instrumentation.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".