Longitudinal profile of the <scp>Upper Weihe River</scp>: Evidence for the late <scp>Cenozoic</scp> uplift of the northeastern <scp>Tibetan Plateau</scp>
Bibliographic record
Abstract
The Upper Weihe River (UP‐WHR) basin is located along the northeastern Tibetan Plateau. With the northeastward expansion of the Tibetan Plateau since the late Cenozoic, it has involved foreland propagation and undergone obvious surface uplift. In order to determine the latest differential rock uplift and river incision, longitudinal profiles for 12 major tributaries of the UP‐WHR were extracted. Among them, 11 tributaries display uneven profiles with “slope‐break” knickpoints, suggesting that they are in a transient state and that the change in base level caused by tectonic forces may respond to the channel evolution. In addition, channel steepness index (ksn) was calculated to detect the spatial variations of the rock uplift rate. The results show that the north margin of West Qinling (WQL) and the south Liupan Shan (LPS) areas have a high uplift rate. Reconstruction of the paleochannel indicates that the Weihe River has an average incision of 354 ± 130 m since it formed, and the south tributaries have a higher incision of 144 ± 25 m than the north. An average river erosion rate of 0.25–0.3 m/ka was estimated, the WQL has a higher erosion rate of 0.1–0.12 m/ka than Longzhong Basin and the south LPS. This uplift and river incision can be correlated to the northeastward growth of the Tibetan Plateau since the late Cenozoic.
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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".