How retrogressive thaw slumps change over time - a study from Herschel Island (Canada) using 3D electrical resistivity tomography (ERT)
Bibliographic record
Abstract
Retrogressive thaw slumps (RTS) are a common thermokarst landform along arctic coastlines with an increasing thermoerosional activity. They underlay a rapid change in topographical as well as internal structures due to various external factors, e.g. changing climate conditions. In 2011 and 2019 electrical resistivity tomography (ERT) measurements were carried during field campaigns to Herschel Island (Yukon Territory, Canada). Transects crossing Herschel Islands largest slump were performed, as well as quasi 3D-ERT-profiles. For better understanding these changes we compared the datasets focusing on the internal structures just as variations in the topography. The aim for our study is gaining an impression of structural and topographical changes over several years, leading towards a better comprehension of long-term processes in retrogressive thaw slumps.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".