MétaCan
Menu
Back to cohort
Record W3194878883 · doi:10.1029/2021jf006306

Modeling Ice‐Crystal Fabric as a Proxy for Ice‐Stream Stability

2021· article· en· W3194878883 on OpenAlexaff
David A. Lilien, Nicholas Rathmann, Christine S. Hvidberg, Dorthe Dahl‐Jensen

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Manitoba
FundersVillum Fonden
KeywordsProxy (statistics)Ice crystalsGeologyMaterials scienceMeteorologyGeographyComputer science

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.091
GPT teacher head0.333
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations39
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Geophysical Research Earth SurfaceSame topicCryospheric studies and observationsFrench-language works237,207