Impact of environmental factors on the distribution of extreme scouring (gouging) events, Canadian Beaufort Shelf
Bibliographic record
Abstract
Seabed repetitive mapping surveys between 1979 and 1990 and again from 2001 to 2008 have led to the identification of 17,047 new ice scour (gouge) events across the Canadian Beaufort Shelf. Of these, 290 are extreme scour events with depths ≥ 2.0 m, which represents approximately 1.7% of the total new scour population. Extreme scour events were spatially correlated with geotechnical zonation, bathymetry, shelf gradient, seabed sediment type, surficial sediment thickness, and sea-ice regime. The Beaufort shelf is divided into four geotechnical regions: Eastern Shelf, Western Shelf, Mackenzie Trough and Yukon Shelf. Of the 290 extreme scours, 9 occur in the Eastern Shelf region, 275 occur in the Western Shelf region, 2 in the Mackenzie Trough and 4 on the Yukon Shelf. Bathymetrically, extreme scours occur between 17m to 36m on the Eastern Shelf and 11m to 50m water depth on the Western Shelf. Extreme scours in the Mackenzie Trough occur between 14m to 17m of water, and 29m to 33m on the Yukon Shelf. In general, gouge depth increases with decreasing surficial sediment grain size. Almost 96% of the extreme scours occur in clay. Sub-bottom profiler data provides evidence that a relatively thick sequence of sediments overlying a competent layer allows for deeper scours. The regional gradient of the Canadian Beaufort Shelf is very low with a ratio of approximately 1m per 1km. The low gradient is shelf wide and does not appear to have a major impact on the spatial distribution of extreme events. From a sea-ice perspective, the majority of extreme events are confined to the transition zone between 8m and 35m water depth where multiyear and first year ice ridging is most prevalent. Bathymetry, ice-regime and geotechnical zonation factors show the greatest correlations with extreme events. They combine to limit the spatial distribution of extreme scour (gouge) events. These factors may also play a role in limiting the depth of these extreme ice scouring events.
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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 | 0.000 | 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) | 0.002 | 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".