Impact of the global warming on the fluvial thermal erosion over the Lena River in Central Siberia
Bibliographic record
Abstract
The hydrology of the Lena and its tributaries is characterized by an extremely episodic flow regime. Here we report recent climatic change in Central Siberia, and its impact on the fluvial thermal erosion. We point out three major changes since the 1980s: a marked reduction of the river ice thickness in winter, a pronounced increase of the water stream temperature in spring and a slight increase of the discharge during the break up (May–June). A GIS analysis based on aerial pictures and satellite images highlights the impact of the water warming on the frozen banks. The vegetated islands appear to be very sensitive to the water temperature increase, showing an acceleration of their head retreat (+21–29%). This suggests that recent global warming directly affects the fluvial dynamics and the erosional process of one of the largest arctic fluvial system.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".