Electrical and electromagnetic data for permafrost characterization at Iqaluit International Airport, Nunavut
Bibliographic record
Abstract
Iqaluit International Airport presently suffers from instabilities and subsidence along its runway, taxiways and apron. In particular, asphalt surfaces are significantly impacted by settlement and cracking These instabilities may be related to permafrost, permafrost degradation and associated drainage conditions. This Open File reports on electrical and electromagnetic geophysical data collected and processed by the Geological Survey of Canada at the Iqaluit International Airport as part of the Land-Based Infrastructure Project within the Climate Change Geoscience Program. Galvanic and capacitive electrical resistivity surveys, along with low induction number electromagnetic measurements, were performed over selected areas within the airport boundary and in the near vicinity to assist with permafrost characterization and to investigate active permafrost processes. The recovered electrical resistivities suggest distinct electrical signatures for different terrain units and sediment types, and for ice-rich material including ice wedges. Even with continuous permafrost and cold permafrost temperatures, the resistivity models reveal anomalously conductive material at depth that is not obviously correlated to mapped surficial sediments. The anomalous regions are correlated with localized settlement problems and downward multi-season displacement derived from D-InSAR. The geophysical surveys also exhibit features indicative of seasonal freezing of localized groundwater beneath airport infrastructure and variable active layer thickness under infrastructure that is thicker than for undeveloped ground.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".