Induced polarization as a tool to characterize permafrost. 2. Applications to low and high-porosity environments
Bibliographic record
Abstract
SUMMARY In the previous paper of this series, a petrophysical model named the Dynamic Stern Layer (DSL) model was extended to describe induced polarization phenomena associated with permafrost by capturing direct and indirect effects associated with the presence of ice in porous media. In this paper, time-domain induced polarization data obtained in field conditions are interpreted thanks to this updated DSL model. We selected three different test sites in order to apply the DSL model to very different conditions of low and high ice contents to see how ice content directly and indirectly affects geoelectrical measurements. A first survey is performed along a cross-section of a ridge in the Kangerlussuaq mountains of Greenland (Site I). In this area, the rock corresponds to a Precambrian granite characterized by a rather low (<5 per cent) porosity and therefore a low ice volumetric content on the North face of the ridge. We do not see any direct ice polarization contribution in the data obtained with a current injection period of 1 s. We also performed a field survey close to Col des Vés (2846 m a.s.l., Tignes, French Alps, Site II). This site corresponds to a complex ground ice body overlying a substratum made of a low-porosity marble, both having high resistivity values. The front of this body is characterized by a small amount of residual ice while the roots are ice-rich. Therefore the porosity at this site is high and the ice content highly variable. This case study showcases the role of ice in the induced polarization data in terms of high chargeability values (close to 1 as predicted by the theory in which ice behaves as a surfacic protonic semiconductor) at the roots of the complex ground ice body. A third site (Site III) corresponds to a profile crossing the Aiguille du Midi (3842 m a.s.l., Chamonix), also in the French Alps in a low porosity granitic environment. Laboratory experiments are used to interpret the tomograms of the electrical conductivity and normalized chargeability using the DSL model and water content and cation exchange capacity tomograms are reconstructed at these sites. This study demonstrates the ability of induced polarization to be an efficient tool to characterize permafrost in very different field conditions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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 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".