Lithospheric-scale anisotropies control first-order stress orientation during Cretaceous-Cenozoic plate kinematics in Western-Central Europe
Bibliographic record
Abstract
Late Mesozoic-Cenozoic plate convergence led to widespread intraplate deformation in Western-Central Europe during the Late Cretaceous-Paleogene and the Miocene until today reflecting the collision of Eurasia with Iberia-Africa and Adria, respectively. The resulting complex deformation pattern inside the plate boundary zone contrasts with a rather uniform orientation adjacent to the north. Although there is broad consensus that the orientation of the first-order stress is controlled by plate kinematics, there is no sufficient explanation for the variation of the stress field across the plate boundary. We model plate kinematic trajectories and analyze the spatial distribution of paleostress data from fault-slip inversion and tectonic stylolites. The comparison reveals the coexistence of two contrasting stress provinces in Europe throughout the Late Mesozoic-Cenozoic. Inside the diffuse plate boundary zone, trajectories of plate motion fit deformation patterns. Outside of that zone, however, there is significant deviation. Here deformation is mainly accommodated by the reactivation of Paleozoic shear zones. Thus, we argue that lithospheric-scale structural inheritance from the Pangea assemblage controls the stress-strain pattern of Western-Central Europe between the active plate boundary zone and the East European Craton since the Late Mesozoic.
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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 | 0.001 | 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".