Tectonic slicing of subducting oceanic crust along plate interfaces: Numerical modeling
Bibliographic record
Abstract
Abstract Multikilometer‐sized slivers of high‐pressure low‐temperature metamorphic oceanic crust and mantle are observed in many mountain belts. These blueschist and eclogite units were detached from the descending plate during subduction. Large‐scale thermo‐mechanical numerical models based on finite difference marker‐in‐cell staggered grid technique are implemented to investigate slicing processes that lead to the detachment of oceanic slivers and their exhumation before the onset of the continental collision phase. In particular, we investigate the role of the serpentinized subcrustal slab mantle in the mechanisms of shallow and deep crustal slicing. Results show that spatially homogeneous serpentinization of the sub‐Moho slab mantle leads to complete accretion of oceanic crust within the accretionary wedge. Spatially discontinuous serpentinization of the slab mantle in form of unconnected patches can lead to shallow slicing of the oceanic crust below the accretionary wedge and to its deep slicing at mantle depths depending on the patch length, slab angle, convergence velocity and continental geothermal gradient. P‐T paths obtained in this study are compared to natural examples of shallow slicing of the Crescent Terrane below Vancouver Island and deeply sliced crust of the Lago Superiore and Saas‐Zermatt units in the Western Alps.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".