Geophysical mapping of ground ice using a combination of capacitive coupled resistivity and ground‐penetrating radar, Northwest Territories, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The nature and distribution of ground ice are two of the most unpredictable geological variables in near‐surface deposits characterized by continuous permafrost. Subsurface information about ground ice distribution and structure can be obtained either by invasive and environmentally destructive techniques like drilling and excavation or by noninvasive low‐impact geophysical methods. In this study, coordinated measurements by two complementary geophysical tools, capacitive‐coupled resistivity (CCR) and ground‐penetrating radar (GPR) were used to map ground ice in a variety of locations in the Mackenzie Delta region of the western Canadian Arctic. Both CCR and GPR systems are highly portable (especially on snow covered surfaces) and very effective in collecting data under winter conditions when cold ground temperatures ensure that nearly all liquid water is frozen and signal penetration is enhanced. CCR and GPR readily detect stratigraphic differences including the contacts between massive ice deposits and enclosing sediments. GPR is widely used in permafrost research, but CCR has been used in only a few studies. This is the first study to combine results from both systems by collecting complementary data sets along coincident transects. We demonstrate that when combined, these data increase the quality and interpretation of subsurface information beyond what could be determined by either of the instruments alone. The complementary nature of these two geophysical tools facilitated the detection and mapping of massive ground ice, ice‐rich sediments, ice wedges, thermokarst, and basic stratigraphic relationships. This study breaks new ground by documenting the benefits of using these techniques together in permafrost investigations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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