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Record W2069128811 · doi:10.1029/2009jf001329

Dynamics and mass balance of Taylor Glacier, Antarctica: 2. Force balance and longitudinal coupling

2009· article· en· W2069128811 on OpenAlexaff
Jeffrey L. Kavanaugh, Kurt M. Cuffey

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGlacierGeologyForcing (mathematics)AmplitudeGeomorphologyGlacier ice accumulationIce streamGlacier mass balanceMechanicsGeodesyClimatologyPhysicsCryosphereSea ice

Abstract

fetched live from OpenAlex

Taylor Glacier, Antarctica, exemplifies an ice sheet outlet that flows through a region of rugged topography and dry climate. In contrast to other well‐studied outlets, Taylor Glacier moves very slowly, despite a thickness of order 1 km and driving stresses averaging 1.5 bars. Here we analyze new measurements of glacier geometry and surface velocity to elucidate flow dynamics of Taylor Glacier. Force balance and basal temperatures are calculated at six locations along the glacier's length using an algorithm developed for this study. The effects of stress‐gradient coupling on longitudinal flow variations are also examined; we ask whether Kamb and Echelmeyer's (1986) linearized theory adequately describes the observed response of flow to large‐amplitude variations in driving stress. The force balance calculations indicate that no basal motion is needed to explain the observed flow of Taylor Glacier. Inferred basal temperatures are within a few degrees of the melting point in regions of kilometer‐thick ice and well below the melting point elsewhere; deformation of subfreezing ice largely controls the flow of Taylor Glacier. Basal drags are mostly in the range 0.9 to 1.2 bars, and lateral drags are in the range 0.2 to 0.5 bar. Stress‐gradient coupling strongly reduces the variability of velocities along the glacier. The velocity variations can be described as the convolution of a forcing function with a spatial filter, as Kamb and Echelmeyer suggested, but the form of the forcing function differs from the theoretical relation derived for small‐amplitude perturbations (the power on driving stress is one, not three).

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 score0.010
Threshold uncertainty score0.019

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 head0.030
GPT teacher head0.294
Teacher spread0.264 · 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
Published2009
Admission routes1
Has abstractyes

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