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Record W1711479033 · doi:10.1029/2009gc002949

Pore fluid modeling approach to identify recent meltwater signals on the west Antarctic Peninsula

2010· article· en· W1711479033 on OpenAlexaff
Zunli Lu, Rosalind E. M. Rickaby, Julia S. Wellner, R. Bastian Georg, Norman Charnley, John B. Anderson, Christian Hensen

Bibliographic record

VenueGeochemistry Geophysics Geosystems · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsTrent University
FundersNatural Environment Research CouncilSight Research UK
KeywordsMeltwaterGeologyGlacierFjordMoraineIce sheetGlacier ice accumulationGlacial periodGlacier morphologyOceanographyIce coreIce streamSea iceClimatologyCryosphereGeomorphology

Abstract

fetched live from OpenAlex

The sensitivity of sea level to melting from polar ice sheets and glaciers during recent natural and anthropogenic climate fluctuations is poorly constrained beyond the period of direct observation by satellite. We have investigated glacial meltwater events during the Anthropocene by adapting the pioneering approach of modeling trends in δ 18 O in the pore waters of deep‐sea cores, previously used to constrain the size of ice sheets during the Last Glacial Maximum. We show that during recent warm periods, meltwater from glacier retreat drains into the coastal fjords, leaving a signature of depleted δ 18 O values and low Cl concentrations in the pore water profiles of rapidly accumulating sediments. Here we model such pore water profiles in a piston core to constrain the timing and magnitude of an ice sheet retreat event at Caley Glacier on the west Antarctic Peninsula, and the result is compared with local ice front movement. This approach of pore water modeling was then applied in another kasten core and tested by a series of sensitivity analyses. The results suggest that our approach may be applied in fjords of different sedimentary settings to reconstruct the glacier history and allow insight into the sensitivity of polar glaciers to abrupt warming events.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.029
GPT teacher head0.235
Teacher spread0.205 · 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.

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

Citations5
Published2010
Admission routes1
Has abstractyes

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