Controls on the Thermomechanical Evolution of Hyperextended Lithosphere at Magma‐Poor Rifted Margins: The Example of Espirito Santo and the Kwanza Basins
Bibliographic record
Abstract
Abstract High‐quality, long offset seismic data from many distal rifted margins show evidence for hyper‐extended, <10‐km‐thick crust. Direct observation of such domains is challenging as they lie, at great water depth, buried beneath thick sedimentary sequences and formed by rock‐assemblages that are hydrated and geophysically indistinguishable. Only a few drill holes have penetrated basement at ultradistal rifted margins. These observations, together with outcrops of preserved analogs exposed in collisional orogens, suggest that the complex interaction of detachment faults rooted in a subhorizontal shear zone in the hyperextended crust or, in the serpentinized mantle controls the formation of the ocean continent transition. While depth‐dependent thinning controls the early phases of rifting conforming to classical rift models, we still have a superficial understanding of how normal faults and subhorizontal shear zones form and evolve during rifting and lithospheric breakup. Here we develop a rheological parameterization to simulate the formation of, and slip‐on, large offset normal faults rooted in growing brittle to ductile shear zones. The evolution of these structures leads to the creation of a hyperextended crust and eventually exhumed serpentinized mantle. We also propose a simplified formulation to simulate magmatic underplating and seafloor spreading. The resulting numerical models provide a self‐consistent picture for the evolution of magma‐poor rifted margins from initiation of rifting to seafloor spreading. The model results are compared with first‐order observations of the Kwanza and Espirito Santo conjugate margins in the South Atlantic as well as of magma‐poor margins globally.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".