Advances in geophysical methods for permafrost investigations
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Bibliographic record
Abstract
Abstract Geophysical techniques can be used to examine the spatial distribution of subsurface geophysical properties to delineate horizontally and vertically the active layer, permafrost and taliks. Spatial and temporal changes in subsurface geophysical properties due to permafrost cooling, warming, aggradation or degradation can also be assessed through geophysical monitoring. This paper reviews the geophysical methods most frequently applied in mountain and arctic/subarctic lowland permafrost investigations. Key results and recommendations based on the analysis of the applicability and reliability of different geophysical techniques for permafrost studies are summarised. Emphasis is put on the tomographic capabilities of geophysical methods. Recent advances in application and data interpretation are shown in relation to five case studies, and future perspectives are highlighted. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it