Evolution of the Yangtze River network, southeastern Tibet: Insights from thermochronology and sedimentology
Bibliographic record
Abstract
Abstract We performed apatite and zircon (U-Th)/He dating on a granitic pluton that has been offset by ∼10 km by motion on the sinistral strike-slip Xiangcheng fault in SW Sichuan, SE Tibetan plateau, where the Shuoqu River incises a deep valley before joining the upper Yangtze River. Mean ZHe cooling ages range from 49.5 ± 2.2 Ma to 68.6 ± 6.0 Ma. Samples located above 3870 m yield mean apatite (U-Th)/He ages ranging from 30.6 ± 1.4 Ma to 40.6 ± 2.7 Ma, whereas samples at lower elevations range from 9.8 ± 1.3 Ma to 14.6 ± 2.7 Ma. In the same region, Cenozoic continental sediments are exposed on the flanks of deep valleys. They consist of unsorted conglomerates and sandstones that partly fill a paleotopography. The sediments were deposited during an episode of rapid sedimentation, followed by incision that varies between 0.5 and 1.2 km. Thermal and exhumational modeling of the granite thermochronometric data indicates rapid cooling during the middle Miocene that was likely related to fluvial incision. Our findings suggest that the upper Yangtze River and its tributary (Shuoqu) were connected by the middle Miocene. Our modeling also supports the idea that the exhumation pattern during the Cenozoic in the southeastern margin of the Tibetan Plateau is spatially and temporally heterogeneous.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 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".