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Record W3200861724 · doi:10.1029/2021gl094762

Isolated Cavities Dominate Greenland Ice Sheet Dynamic Response to Lake Drainage

2021· article· en· W3200861724 on OpenAlexaff
Jessica Mejía, Jason Gulley, Celia Trunz, M. D. Covington, T. C. Bartholomaus, Surui Xie, Timothy H. Dixon

Bibliographic record

VenueGeophysical Research Letters · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversité de Sherbrooke
FundersNational Science Foundation
KeywordsGreenland ice sheetGeologyMeltwaterIce sheetGlacierDrainageDewateringGeomorphologyChannelizedHydrology (agriculture)Geotechnical engineeringEcology

Abstract

fetched live from OpenAlex

Abstract Seasonal variability in the Greenland Ice Sheet's (GrIS) sliding speed is regulated by the response of the subglacial drainage system to meltwater inputs. However, the importance of channelization relative to the dewatering of isolated cavities in controlling seasonal ice deceleration remains unsolved. Using ice motion, moulin hydraulic head, and glaciohydraulic tremor measurements, we show the passing of a subglacial floodwave triggered by upglacier supraglacial lake drainages slowed sliding to wintertime background speeds without increasing the hydraulic capacity of the moulin‐connected drainage system. We interpret these results to reflect an increase in basal traction caused by the dewatering of isolated cavities. These results suggest the dewatering of isolated parts of the subglacial drainage system play a key role in driving seasonal slowdowns on the GrIS.

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 score0.018
Threshold uncertainty score0.035

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.285
Teacher spread0.260 · 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

Citations31
Published2021
Admission routes1
Has abstractyes

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