Hydrochemical coupling of a glacial borehole–aquifer system
Bibliographic record
Abstract
Abstract Measurements of the electrical conductivity of subglacial water provide a useful complement to measurements of pressure and turbidity. In the summer season, fluctuations of conductivity can be attributed to changes in water transport, water provenance and subglacial residence time. These explanations are unlikely to apply during the winter season because surface melt sources are not active and the subglacial water system is predominantly unconnected. Thus, fluctuations in water conductivity during the winter months seem paradoxical. To introduce a quantitative basis for comprehending such phenomena, we develop an interpretative model of the hydrochemical interaction between a water-filled borehole and a subglacial aquifer. The electrical conductivity of water near the borehole–aquifer contact is affected not only by diffusion but also by advective transport of solute between the two reservoirs in response to pressure forcing of the system. Using records of ice strain, water pressure and electrical conductivity from unconnected boreholes in Trapridge Glacier, we demonstrate that changes in borehole geometry caused by ice-strain events provide a plausible mechanism for at least some of the observed fluctuations of electrical conductivity. Conductivity records provide information regarding advective coupling of the borehole–aquifer system that is not available from pressure records alone.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".