The Origin of Forearc Depressions
Bibliographic record
Abstract
Forearc depressions form over continental subduction zones with young, slowly subducting slabs and thick trench fills. They are bound seaward by a coast range and landward by a volcanic arc such that subsidence in forearc depressions occurs between orogens and in areas characterized by plate convergence. We propose a model for forearc depression formation based on geophysical and seismic data from four circum-Pacific subduction zones. Coast range crests coincide with >100 mGal gravity anomalies, which are attributed to underplated material and indicate that underplating drives coast range uplift. Coast range crests are situated near the down-dip termini of megathrust earthquake rupture zones, showing that coast ranges overlie where subduction interface sliding behaviour transitions from frictional to semi-frictional. This transition causes subduction interface shear stress to begin decreasing with depth and triggers underplating as shear stress becomes insufficient to drag buoyant material deeper. Forearc depressions are situated landward of inter-plate seismic phenomena, indicating they overlie the hydrated forearc mantle. Forearc depressions form as counter-flexural basins over the hydrated forearc mantle; in this position the upper plate crust is not supported by the flexurally rigid slab and can bend downwards. Forearc depressions do not form over old slabs because old slabs do not exceed the temperature threshold for semi-frictional sliding prior to intersecting the mantle wedge corner. Fast convergence rates and thin trench fills promote subduction erosion along the subduction interface, thereby prohibiting the formation of coast ranges, and by extension, forearc depressions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".