Simulating higher-order fabric structure in a coupled, anisotropic ice-flow model: application to Dome C
Bibliographic record
Abstract
Abstract Ice-crystal fabric can induce mechanical anisotropy that significantly affects flow, but ice-flow models generally do not include fabric development or its effect upon flow. Here, we incorporate a new spectral expansion of fabric, and more complete description of its evolution, into the ice-flow model Elmer/Ice. This approach allows us to model the effect of both lattice rotation and migration recrystallization on large-scale ice flow. The fabric evolution is coupled to flow using an unapproximated non-linear orthotropic rheology that better describes deformation when the stress and fabric states are misaligned. These improvements are most relevant for simulating dynamically interesting areas, where recrystallization can be important, tuning data are scarce and rapid flow can lead to misalignment between stress and fabric. We validate the model by comparing simulated fabric to ice-core and phase-sensitive radar measurements on a transect across Dome C, East Antarctica. With appropriately tuned rates for recrystallization, the model is able to reproduce observations of fabric. However, these tuned rates differ from those previously derived from laboratory experiments, suggesting a need to better understand how recrystallization acts differently in the laboratory compared to natural settings.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".