Utilizing Euler poles for the evaluation of plate rigidity in numerical mantle convection models
Bibliographic record
Abstract
We implement an innovative method of plate identification for the purpose of evaluating plate motion in numerical mantle convection models. Our method utilizes an existing tool, Automatic Detection Of Plate Tectonics (ADOPT), which applies a tolerance (threshold) algorithm to elevation maps, to detect candidate plate boundaries at the surface of 3-D spherical mantle convection models. The logarithm of the strain-rate field yields a well-defined elevation map where local maxima lineations indicate spreading centres, zones of convergence, transform faults or diffuse deformation zones. For the plates found by ADOPT’s analysis, we determined rotation (Euler) poles implied by the velocities within the plate interiors. Subsequently, we examined the velocity field of each model plate for its agreement with rigid motion about the Euler poles. We apply our method to snapshots taken from three previously published mantle convection calculations that appear to generate plate-like surface behaviour. Self-consistently generated model plates were obtained by combining a highly temperature-dependent viscosity with a yield stress that adds a strain-rate dependence to the viscosity, thus allowing for both intra-plate low strain-rate and weakening along tightly focussed plate boundaries. We generally identify more (and smaller) rigid plates for low yield stress or low threshold. Strong agreement of the surface velocities with rigid-body rotation around Euler poles is found for many of the plates identified; however, some plates also exhibit internal deformation. Regions that show a departure from rigidity can be decomposed into subsets of rigidly moving plates. Thus, the identification of a mantle convection model's maximally rigid plate surface may require plate boundary detection at both low and high thresholds. We suggest that as global mantle convection models superficially converge on the generation of plate boundary network similar to those observed with plate tectonics (including transform fault generation), testing for plate rigidity through the determination of Euler poles can serve as a quantitative measure of plate-like surface motion.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".