MétaCan
Menu
← Back to cohort
Record W4392654133 · doi:10.5194/egusphere-egu24-18028

Folded ice in the upper North East Greenland Ice Stream reveal timing of the onset of streaming

2024· preprint· en· W4392654133 on OpenAlexaff
Daniela Jansen, Steven Franke, Catherine Bauer, Tobias Binder, Dorthe Dahl‐Jensen, Jan Eichler, Olaf Eisen, Yuanbang Hu, Johanna Kerch, María-Gema Llorens, Heinrich Miller, Niklas Neckel, John Paden, Tamara de Riese, Till Sachau, Nicolas Stoll, Ilka Weikusat, Frank Wilhelms, Yu Zhang, Paul D. Bons

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGeologyIce streamClimatologyPhysical geographyIce coreIce sheetCryosphereOceanographySea iceGeography

Abstract

fetched live from OpenAlex

Only a few localised ice streams drain most ice from the Greenland Ice Sheet. Thus, understanding ice stream behaviour and their temporal variability is crucially important to predict future sea-level change. The interior trunk of the 700 km-long North-East Greenland Ice Stream (NEGIS) is remarkable for the lack of any clear bedrock channel to explain its presence. Here we use isochronous radar reflections from an airborne radar survey as passive tracers of ice deformation. We present the first-ever 3-dimensional analysis of folding and advection of stratigraphic horizons within an ice stream, which shows that the localised flow and shear margins in the upstream part were fully developed only ca. 2000 years ago. This indicates that this type of streaming in the interior of an ice sheet can be triggered on short time scales.

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 score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.036
GPT teacher head0.237
Teacher spread0.201 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicCryospheric studies and observations→French-language works237,207→