Crustal thickness variations and isostatic disequilibrium across the North Anatolian Fault, western Turkey
Bibliographic record
Abstract
Abstract We use teleseismic recordings from a dense array of seismometers straddling both strands of the North Anatolian Fault Zone to determine crustal thickness, P/S velocity ratio and sedimentary layer thickness. To do this, we implement a new grid search inversion scheme based on the use of transfer functions, removing the need for deconvolution for source normalization and therefore eliminating common problems associated with crustal‐scale receiver function analysis. We achieve a good fit to the data except at several stations located in Quaternary sedimentary basins, where our two‐layer crustal model is likely to be inaccurate. We find two zones of thick sedimentary material: one north of the northern fault branch, and one straddling the southern branch. The crustal thickness increases sharply north of the northern strand of the North Anatolian Fault Zone (NAFZ), where the fault nearly coincides with the trace of the Intra‐Pontide Suture; the velocity ratio changes across the southern fault strand, indicating a change in basement composition. We interpret these changes to indicate that both strands of the NAFZ follow preexisting geological boundaries rather than being ideally aligned with the stress field. The thick crust north of the northern NAFZ strand is associated with low topography and so is inconsistent with simple models of isostatic equilibrium, requiring a contribution from mantle density variations, such as possible loading from underthrust Black Sea oceanic lithosphere.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".