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Record W4375954632 · doi:10.1038/s41467-023-38139-8

Crystal orientation fabric anisotropy causes directional hardening of the Northeast Greenland Ice Stream

2023· article· en· W4375954632 on OpenAlexafffund
Tamara Annina Gerber, David A. Lilien, Nicholas Rathmann, Steven Franke, Tun Jan Young, Fernando Valero-Delgado, M. Reza Ershadi, Reinhard Drews, Ole Zeising, Angelika Humbert, Nicolas Stoll, Ilka Weikusat, Aslak Grinsted, Christine S. Hvidberg, Daniela Jansen, Heinrich Miller, Veit Helm, Daniel Steinhage, Charles O’Neill, John Paden, Siva Prasad Gogineni, Dorthe Dahl‐Jensen, Olaf Eisen

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Manitoba
FundersNovo Nordisk FondenNational Institute of Polar ResearchUniversitetet i BergenInstitut Polaire Français Paul Emile VictorBeijing Normal UniversityUniversity of AlabamaCanada Excellence Research Chairs, Government of CanadaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungDeutsche ForschungsgemeinschaftTrond Mohn stiftelseVillum FondenChinese Academy of SciencesDeutscher Akademischer AustauschdienstA.P. Møller og Hustru Chastine Mc-Kinney Møllers Fond til almene FormaalNational Science Foundation
KeywordsAnisotropyGeologyIce streamIce sheetIsotropyIce crystalsShear (geology)GeomorphologyMineralogySea icePetrologyMeteorologyCryosphereOpticsClimatologyPhysics

Abstract

fetched live from OpenAlex

The dynamic mass loss of ice sheets constitutes one of the biggest uncertainties in projections of ice-sheet evolution. One central, understudied aspect of ice flow is how the bulk orientation of the crystal orientation fabric translates to the mechanical anisotropy of ice. Here we show the spatial distribution of the depth-averaged horizontal anisotropy and corresponding directional flow-enhancement factors covering a large area of the Northeast Greenland Ice Stream onset. Our results are based on airborne and ground-based radar surveys, ice-core observations, and numerical ice-flow modelling. They show a strong spatial variability of the horizontal anisotropy and a rapid crystal reorganisation on the order of hundreds of years coinciding with the ice-stream geometry. Compared to isotropic ice, parts of the ice stream are found to be more than one order of magnitude harder for along-flow extension/compression while the shear margins are potentially softened by a factor of two for horizontal-shear deformation.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.262
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations44
Published2023
Admission routes2
Has abstractyes

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