Bibliographic record
Abstract
Abstract. Along much of the Arctic coast, shoreline retreat and sea level rise combine to inundate permafrost. Once inundated by seawater permafrost usually begins to degrade. Tuktoyaktuk Island (Beaufort Sea, NWT, Canada) is an important natural barrier protecting the harbor of Tuktoyaktuk, but will likely be breached within the next three decades. The state of subsea permafrost and its depth distribution around the island are, however, still largely unknown. We collected marine electrical resistivity tomography (ERT) surveys (vertical electrical soundings) north and south of Tuktoyaktuk Island using a floating cable with 13 electrodes in a quasi-symmetric Wenner-Schlumberger array. We filtered the data with a new approach to eliminate potentially falsified measurements due to a curved cable and inverted the profiles with a variety of parameterizations to estimate the position of the top of the ice-bearing permafrost table (IBPT) below the sea floor. Our results indicate that north of Tuktoyaktuk Island, where coastal erosion is considerably faster, IBPT depths range from 5 m below sea level (120 m from the shoreline) to around 20 m bsl (up to 800 m from the shoreline). South of the island, the IBPT dips more steeply and lies at 10 m bsl a few meters from the shore to more than 30 m bsl 200 m from the shore. We discuss how marine ERT measurements can be improved by recording electrode position, but choices made in data inversion can be a more likely source of uncertainty in IBPT position than electrode positions. At Tuktoyaktuk Island, IBPT depths below the sea floor increase with distance from the shoreline; comparing the northern and southern sides of the island, its inclination is inversely proportional to coastline retreat rates. On the island’s north side, historical coastal retreat rate suggests a mean degradation rate of 5.3 ± 4.0 cm/yr.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.015 | 0.007 |
| Insufficient payload (model declined to judge) | 0.523 | 0.399 |
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".