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Record W4296896569 · doi:10.1038/s41467-022-32999-2

Accelerating ice flow at the onset of the Northeast Greenland Ice Stream

2022· article· en· W4296896569 on OpenAlexaff
Aslak Grinsted, Christine S. Hvidberg, David A. Lilien, Nicholas Rathmann, Nanna B. Karlsson, Tamara Annina Gerber, Helle Astrid Kjær, Paul Vallelonga, Dorthe Dahl‐Jensen

Bibliographic record

VenueNature Communications · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Manitoba
FundersOffice of Polar ProgramsNational Science FoundationA.P. Møller og Hustru Chastine Mc-Kinney Møllers Fond til almene FormaalUniversitetet i BergenInstitut Polaire Français Paul Emile VictorBeijing Normal UniversityTrond Mohn stiftelseChinese Academy of SciencesNational Institute of Polar ResearchSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungVillum FondenMiljøstyrelsen
KeywordsIce streamIce coreGeologyGroenlandiaFlow (mathematics)Physical geographyIce sheetOceanographyCryosphereSea iceGeographyPhysics

Abstract

fetched live from OpenAlex

Mass loss near the ice-sheet margin is evident from remote sensing as frontal retreat and increases in ice velocities. Velocities in the ice sheet interior are orders of magnitude smaller, making it challenging to detect velocity change. Here, we analyze a 35-year record of remotely sensed velocities, and a 6-year record of repeated GPS observations, at the East Greenland Ice-core Project (EastGRIP), located in the middle of the Northeast-Greenland Ice Stream (NEGIS). We find that the shear margins of NEGIS are accelerating, indicating a widening of the ice stream. We demonstrate that the widening of the ice stream is unlikely to be a response to recent changes at the outlets of NEGIS. Modelling indicates that the observed spatial fingerprint of acceleration is more consistent with a softening of the shear margin, e.g. due to evolving fabric or temperature, than a response to external forcing at the surface or bed.

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 score0.073
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.250
Teacher spread0.217 · 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

Citations34
Published2022
Admission routes1
Has abstractyes

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