Asthenospheric flow estimates in the Atlantic realm based on Poiseuille/Couetteflow models
Bibliographic record
Abstract
Mantle convection has profound effects on the Earth’s surface, such as inducing vertical motion, which is commonly termed dynamic topography. Sophisticated mantle convection models have been used to study current and past dynamic topography. But many input parameters, like complex rheologies and thermo-chemical flow properties remain poorly known, requiring ad-hoc model parameterization and long range extrapolation. This makes it attractive to explore simple analytic models of upper mantle flow. The existence of a weak asthenosphere allows one to explore upper mantle in the context of Poiseuille/Couette flow. The latter provides an geodynamically plausible link between flow properties and dynamic topography. Here we construct simple upper mantle flow models parameterized in terms of sources/sinks (plumes/slab) of Poiseuille/Couette flow. Our approach provides physical insight into the pattern of upper mantle flow, makes it easy to assess uncertainties of key model parameters, such as poorly resolved asthenospheric thickness and viscosity, and can be extended back in time, given first-order estimates of plume and subduction flux deduced from geological records. Importantly, it demands low computational cost relative to a time dependent geodynamic models. We present results for the Atlantic realm, and link our estimates of upper mantle flow history to Base Hiatus Surfaces (BHS) recently developed by Friedrich etal., (2018), Vibe etal., (2018), Carena etal., (2019), Hayek metal., (2020) and Hayek metal., (2021). The latter serve as proxy for inferring past dynamic topography variations. We also relate our calculations to seismically inferred anisotropy, as a further proxy for upper mantle flow. Our results indicate that asthenospheric flow pattern can be explained through the concept of source to sink and that this flow type is testable against first order seismic and geologic observables. References: Carena, S., Bunge, H. P., & Friedrich, A. M. (2019). Analysis of geological hiatus surfaces across Africa in the Cenozoic and implications for the timescales of convectively-maintained topography. Canadian Journal of Earth Sciences, 56(12), 1333-1346. Friedrich, A. M., Bunge, H. P., Rieger, S. M., Colli, L., Ghelichkhan, S., & Nerlich, R. (2018). Stratigraphic framework for the plume mode of mantle convection and the analysis of interregional unconformities on geological maps. Gondwana Research, 53, 159-188. Hayek, J. N., Vilacís, B., Bunge, H. P., Friedrich, A. M., Carena, S., & Vibe, Y. (2020). Continent-scale Hiatus Maps for the Atlantic Realm and Australia since the Upper Jurassic and links to mantle flow induced dynamic topography. Proceedings of the Royal Society A, 476(2242), 20200390. Hayek, J. N., Vilacís, B., Bunge, H. P., Friedrich, A. M., Carena, S., & Vibe, Y. (2021). Correction: Continent-scale Hiatus Maps for the Atlantic Realm and Australia since the Upper Jurassic and links to mantle flow-induced dynamic topography. Proceedings of the Royal Society A, 477(2251), 20210437. Vibe, Y., Friedrich, A. M., Bunge, H. P., & Clark, S. R. (2018). Correlations of oceanic spreading rates and hiatus surface area in the North Atlantic realm. Lithosphere, 10(5), 677-684.
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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 | 0.000 |
| 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) | 0.001 | 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".