Modeling Ice‐Crystal Fabric as a Proxy for Ice‐Stream Stability
Bibliographic record
Abstract
Abstract The crystal structure within an ice sheet evolves in response to deformation; hence ice‐crystal fabric records ice‐flow history. However, the complexity of crystal‐fabric evolution, and the lack of model results with which to compare data, limit the usefulness of fabric measurements, particularly in areas with complex ice dynamics. Here, we use an ice‐flow model to identify characteristic fabrics associated with ice‐stream onset, with the goal of aiding interpretation of fabric measurements. Using time‐dependent model simulations, we identify how crystal fabric may be used to diagnose changes in an ice stream's speed or lateral position. Consistent with previous work, we find that fabric within an ice stream is generally a vertical girdle, though horizontal shear can lead to a horizontal single maximum. Transient simulations demonstrate that effects from changes in flow may be recorded in the crystal fabric for thousands of years after an ice stream activates and more than ten thousand years after an ice stream stagnates. Both transient and steady effects on fabric are sufficiently large as to be measurable in ice cores or with polarized radar, suggesting that in certain scenarios fabric could be used to identify past flow changes. These results could be used to design radar surveys in areas where ice streams are known to deactivate, such as the Siple Coast in Antarctica, or where they may migrate laterally or widen, such as in Northeast Greenland.
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 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".