Strength of continental lithosphere governed by the time since the last orogeny
Bibliographic record
Abstract
Earth's tectonic history is punctuated by several cycles of supercontinent assembly and breakup that profoundly influenced the lithospheric structure; however, the roles of the various factors controlling continental strength and deformation during the cycles remain debated. The effective elastic thickness (Te) reflects the lithosphere's long-term, depth-integrated strength and is useful for deciphering the complex evolution of continents. In this study, we estimate a new global map of continental Te projected onto a 15′×15′ grid by inverting the cross-spectral properties (admittance and coherence) between Bouguer gravity and topography data obtained from a continuous wavelet transform. Continental Te ranges from <5 to ∼140 km, with a mean and standard deviation of 50 and 33 km, respectively. Based on a gaussian mixture model-based cluster analysis, we delineate tectonically active provinces, stable Archean cratons and transitional lithosphere. We find an obvious positive correlation between Te and lithospheric thickness obtained from calibrated upper mantle surface wave tomography models. Further comparing the Te distribution with orogenic age data shows that Te exhibits a clear time dependence where the strength is governed by the time since the last orogeny. Based on plate cooling models, we indicate that continental Te corresponds approximately to the depth of the 300±150∘C isotherm. These results favour a diffusive (cooling) model that considerably influences the strength of the continental lithosphere, despite the complex relation between Te and the thermal, compositional and rheological structure.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".