Controls of inherited lithospheric heterogeneity on rift linkage: Numerical and analog models of interaction between the Kenyan and Ethiopian rifts across the Turkana depression
Bibliographic record
Abstract
Abstract Inherited rheological structures in the lithosphere are expected to have large impact on the architecture of continental rifts. The Turkana depression in the East African Rift connects the Main Ethiopian Rift to the north with the Kenya rift in the south. This region is characterized by a NW‐SE trending band of thinned crust inherited from a Mesozoic rifting event, which is cutting the present‐day N‐S rift trend at high angle. In striking contrast to the narrow rifts in Ethiopia and Kenya, extension in the Turkana region is accommodated in subparallel deformation domains that are laterally distributed over several hundred kilometers. We present both analog experiments and numerical models that reproduce the along‐axis transition from narrow rifting in Ethiopia and Kenya to a distributed deformation within the Turkana depression. Similarly to natural observations, our models show that the Ethiopian and Kenyan rifts bend away from each other within the Turkana region, thus forming a right‐lateral step over and avoiding a direct link to form a continuous N‐S depression. The models reveal five potential types of rift linkage across the preexisting basin: three types where rifts bend away from the inherited structure connecting via a (1) wide or (2) narrow rift or by (3) forming a rotating microplate, (4) a type where rifts bend towards it, and (5) straight rift linkage. The fact that linkage type 1 is realized in the Turkana region provides new insights on the rheological configuration of the Mesozoic rift system at the onset of the recent rift episode.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".