Poyang and Dongting Lakes, Yangtze River: tributary lakes blocked by main-stem aggradation
Bibliographic record
Abstract
During its 6,300-km course from the Tibetan Plateau to the ocean, the Yangtze River is joined by two large lakes: Dongting Lake and Poyang Lake. We explain why these lakes exist. Deglaciation forced the ocean adjacent to the Yangtze mouth to rise ∼120 m. This forced a wave of rising water surface elevation and concomitant bed aggradation upstream. While aggradation attenuated upstream, the low bed slope of the Middle-Lower Yangtze River (∼2 × 10 −5 near Wuhan) made it susceptible to sea level rise. The main stem, sourced at 5,054 m above sea level, had a substantial sediment load to “fight” against water surface level rise by means of bed aggradation. The tributaries of the Middle-Lower Yangtze have reliefs of approximately hundreds of meters, and did not have enough sediment supply to fill the tributary accommodation space created by main-stem aggradation. We show that the resulting tributary blockage likely gave rise to the lakes. We justify this using field data and numerical modeling, and derive a dimensionless number capturing the critical rate of water surface rise for blockage versus nonblockage.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".