Effects of thermo-erosion gullying on hydrologic flow networks, discharge and soil loss
Bibliographic record
Abstract
Thermo-erosion gullies in continuous permafrost regions where ice-wedge polygons are widespread contribute and change the drainage of periglacial landscapes. Gullying processes are causing long-term impacts to the Arctic landscape such as drainage network restructuring, permafrost erosion, sediment transport. Between 2009 and 2013, 35 gullies were mapped in a polygon terrace in the valley of the Glacier C-79 on Bylot Island, Nunavut (Canada), one of which was monitored for its hydrology. A gully (R08p) initiated in 1999 in a low-center polygon terrace. Between 1999 and 2013, 202 polygons over a surface of 28 891 m ^2 were breached by gullying. Overall, 1401 polygons were similarly breached on the terrace in the valley before 2013. R08p is fed by a 1.74 km ^2 watershed and the hydrological regime is characterized by peak flows of 0.69 m ^3 s ^−1 and a cumulative volume of 229 662 m ^3 for 2013. Historic aerial photography from 1972 and recent field surveys showed a change in the paths of water tracks and an increase in channelized flow in the gully area from none to 35% of the overall flow path of the section. The overall eroded area for the studied gullies in the valley up to 2013 was estimated at 158 000 m ^2 and a potential volume close to 200 000 m ^3 . Gullying processes increased drainage of wetlands and the hydrological connectivity in the valley, while lowering residence time of water near gullied areas.
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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 | 0.000 |
| 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 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".