Electrical Geophysics for Assessing Permafrost Conditions along Highway Infrastructure
Bibliographic record
Abstract
The Yellowknife region, part of the Slave Geological Province, falls within the extensive discontinuous permafrost zone in Canada. A large degree of economic development is routed through Yellowknife from the mineral-rich North Slave. Despite the mineral-rich nature of this region, surficial sediment maps and knowledge of permafrost conditions are only now being established in detail. Permafrost and associated ground ice can significantly affect land-based infrastructure through influence on ground stability and drainage patterns. As such, geoscience information contributing to permafrost characterization is critical for understanding risks to roads which are vital to Northern economic development. The 100 km stretch of the chip-sealed Highway 3, west of Yellowknife, presently experiences instabilities including settlement, heave, and rotations related to transitions between differing terrain and drainage conditions within the discontinuous permafrost. Electrical resistivity data were collected over identified terrain types, and across potential terrain transitions and thaw fronts based on the hypothesis that permafrost distribution and conditions vary with terrain type. Processed resistivity models indicate distinct electrical signatures for most of the terrain types which would allow for extensive geophysical characterization complimentary to landscape mapping, temperature data and shallow boreholes. The resistivity models also exhibit features indicative of the base of ice-bonded permafrost, ice-rich sediment and thaw zones, which can be correlated with terrain features of sediment type and drainage. Observed resistivity anomalies indicate thaw zones related to existing and past road infrastructure, which help in understanding conditions causing highway subsidence.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".