Implications of the fault scaling law for the growth of topography: mountain ranges in the broken foreland of north‐east Tibet
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Bibliographic record
Abstract
Abstract A fault scaling law suggests that, over eight orders of magnitude, fault length L is linearly related to maximum displacement D . Individual faults may therefore retain a constant ratio of D / L as they grow. If erosion is minor compared with tectonic uplift, the length and along‐strike relief of young mountain ranges should thus reflect fault growth. Topographic profiles along the crests of mountain ranges in the actively deforming foreland of north‐east Tibet exhibit a characteristic shape with maximum height near their centre and decreasing elevation toward the tips. We interpret the along‐strike relief of these ranges to reflect the slip distribution on high‐angle reverse faults. A geometric model illustrates that the lateral propagation rate of such mountain ranges may be deciphered if their length‐to‐height ratio has remained constant. As an application of the model, we reconstruct the growth of the Heli Shan using a long‐term uplift rate of ∼1.3 mm yr −1 derived from 21 Ne and 10 Be exposure dating.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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