Tectono‐geomorphic evolution of Harlik Mountain in the Eastern Tian Shan, insight from thermochronological data and geomorphic analysis
Bibliographic record
Abstract
The Harlik Mountain is in the easternmost part of the Tian Shan and is a prime example of an intracontinental orogenic belt. Several studies have used low‐temperature thermochronology to understand the uplift history of this range. However, complicated structures have a profound impact on the study of the tectonic evolution of the Harlik Mountain during the Mesozoic‐Cenozoic. Here, we refine the structural characteristics of the Harlik Mountain and then acquire the detailed thermal histories in different parts of the range. Through field observations, we demonstrate that the brittle Harlik Fault experienced two activities, including early normal faulting and late right‐lateral strike‐slip normal faulting. In particular, geomorphic and river analyses indicate that the topography of the Harlik Mountain was significantly influenced by faults. Combined with the thermochronological data from previous studies, thermal history modelling based on our new data on the Harlik Mountain suggest three fast cooling phases in the 128–110 Ma, 70–55 Ma, and 50–35 Ma. The first and the third cooling phases were associated with fault activities and the second cooling phase was related to regional denudation. The first phase of faulting, in the late Early Cretaceous, may be caused by stress relaxation after the Cimmerian collision. The second phase of faulting was likely to relate to local stress adjustment from the India‐Eurasia collision during the Eocene to Oligocene. Moreover, Late Cretaceous to Palaeocene regional cooling was probably affected by the collision of the Karakoram Block with Eurasia.
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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".