Investigation of Submarine Permafrost Conditions in the Canadian Beaufort Sea Using Diving Wave Tomography
Bibliographic record
Abstract
Abstract Submarine permafrost in the Canadian Beaufort Sea is relict terrestrial permafrost, which is continuously degrading since the change of thermal conditions induced by a marine transgression that followed the last glaciation. Permafrost degradation has a crucial socio‐ecological significance because its thawing can result in geohazards like landslides or an increase in greenhouse gas emissions. These consequences are mostly regulated by the state of ice in permafrost. In this study, we use marine multichannel seismic data to apply a diving wave tomographic inversion on the outer 50 km of the Canadian Beaufort Shelf. Due to the close relationship between seismic velocity and ice content, we are able to infer detailed information about the present submarine permafrost condition. We find a clear variability of permafrost occurrences between the inner and outer Canadian Beaufort Shelf. At the inner shelf, discontinuous ice‐bonding permafrost occurs extensively close to the seafloor but is interrupted by taliks. Within the outer ∼27 km of the shelf, ice‐bonding permafrost is absent in the upper sediments and its top has plunged to >200 m below sea level. These findings add new details to the current state of the degrading permafrost. In addition, we observe seismic anisotropy in the frozen permafrost sediments.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".