Discrimination of the flow law for subglacial sediment using in situ measurements and an interpretation model
Bibliographic record
Abstract
Subglacial hydrological and mechanical processes play a critical role in determining the flow characteristics and stability of glaciers and ice sheets. To study these processes, we have measured simultaneously basal water pressure, pore water pressure, sediment deformation, glacier sliding, and sediment strength beneath Trapridge Glacier, Yukon Territory, Canada. To interpret these data, we have developed a simple hydromechanical model of processes beneath a soft‐bedded alpine glacier. The glacier bed is divided into soft‐bedded regions that are hydraulically connected to the subglacial drainage system, soft‐bedded but hydraulically unconnected regions, and hard‐bedded regions. Each region is represented as a one‐dimensional column. The columns are coupled by a simple ice dynamics model that accounts for water‐pressure‐driven changes in basal shear stress distribution. Synthetic responses for subglacial instruments are calculated from the modeled basal conditions, providing a framework for improving interpretation of field records. The model is used to determine which of several till flow laws best represents conditions beneath Trapridge Glacier. Investigated are linear‐viscous, nonlinear‐viscous, nonlinear‐Bingham, and Coulomb‐plastic tills. Pore water pressures, sediment deformation profiles, and sliding rates are calculated for each flow law. Comparison of synthetic and field instrument responses suggests that till behavior is best represented as Coulomb‐plastic. Model results also suggest that the ploughmeter is the most diagnostic in situ indicator of till behavior currently available and that using long‐term observations of sediment deformation profiles in regions of varying pore water pressure can result in an underestimation of flow law nonlinearity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".