MétaCan
Menu
Back to cohort
Record W4323360842 · doi:10.1029/2022jf006958

Migration of the Shear Margins at Thwaites Glacier: Dependence on Basal Conditions and Testability Against Field Data

2023· article· en· W4323360842 on OpenAlexafffund
Paul T. Summers, Cooper Elsworth, Christine F. Dow, Jenny Suckale

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Waterloo
FundersCanada Research ChairsNatural Environment Research CouncilSight Research UKAchievement Rewards for College Scientists FoundationNational Science Foundation
KeywordsGeologyGlacierThinningGlacier morphologyGeomorphologySea iceIce streamClimatologyCryosphereGeography

Abstract

fetched live from OpenAlex

Abstract Projections of global sea level depend sensitively on whether Thwaites Glacier, Antarctica, will continue to lose ice rapidly. Prior studies have focused primarily on understanding the evolution of ice velocity and whether the reverse‐sloping bed at Thwaites Glacier could drive irreversible retreat. However, the overall ice flux to the ocean and the possibility of irreversible retreat depend not only on the ice speed but also on the width of the main ice trunk. Here, we complement prior work by focusing specifically on understanding whether the lateral boundaries of the main ice trunk, termed shear margins, might migrate over time. We hypothesize that the shear margins at Thwaites Glacier will migrate on a decadal timescale in response to continued ice thinning and surface steepening. We test this hypothesis by developing a depth‐averaged, thermomechanical free‐boundary model that captures the complex topography underneath the glacier and solves for both the ice velocity and for the position of the shear margins. We find that both shear margins are prone to migration in response to ice thinning with basal strength and surface slope steepening determining their relative motion. We construct four end‐member cases of basal strength that represent different physical properties governing friction at the glacier bed and present two cases of ice thinning to contrast the effects of surface steepening and ice thinning. We test our model by hindcasting historic data and discuss how data from ongoing field campaigns could further be used to test our model.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0000.000
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 head0.098
GPT teacher head0.335
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 teacher head, 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

Citations4
Published2023
Admission routes2
Has abstractyes

Explore more

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