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Record W2300975582 · doi:10.5194/tc-10-1883-2016

Persistence and variability of ice-stream grounding lines on retrograde bed slopes

2016· article· en· W2300975582 on OpenAlexafffund
Alexander A. Robel, Christian Schoof, Eli Tziperman

Bibliographic record

Venue˜The œcryosphere · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaDivision of Atmospheric and Geospace SciencesNational Science Foundation
KeywordsGeologyIce streamAntarctic ice sheetFlow (mathematics)InstabilityIce sheetSTREAMSPersistence (discontinuity)GeomorphologyAmplitudeMechanicsGeotechnical engineeringClimatologySea iceCryosphereComputer sciencePhysics

Abstract

fetched live from OpenAlex

Abstract. In many ice streams, basal resistance varies in space and time due to the dynamically evolving properties of subglacial till. These variations can cause internally generated oscillations in ice-stream flow. However, the potential for such variations in basal properties is not considered by conventional theories of grounding-line stability on retrograde bed slopes, which assume that bed properties are static in time. Using a flow-line model, we show how internally generated, transient variations in ice-stream state interact with retrograde bed slopes. In contrast to predictions from the theory of the marine ice-sheet instability, our simulated grounding line is able to persist and reverse direction of migration on a retrograde bed when undergoing oscillations in the grounding-line position. In turn, the presence of a retrograde bed may also suppress or reduce the amplitude of internal oscillations in ice-stream state. We explore the physical mechanisms responsible for these behaviors and discuss the implications for observed grounding-line migration in West Antarctica.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.027
GPT teacher head0.217
Teacher spread0.189 · 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 designSimulation or modeling
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

Citations36
Published2016
Admission routes2
Has abstractyes

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