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Record W4401246529 · doi:10.1126/sciadv.adn1470

The influence of realistic 3D mantle viscosity on Antarctica’s contribution to future global sea levels

2024· article· en· W4401246529 on OpenAlexaff
Natalya Gomez, Maryam Yousefi, David Pollard, Robert M. DeConto, Shaina Sadai, Andrew Lloyd, A. Nyblade, Douglas A. Wiens, R. C. Aster, T. J. Wilson

Bibliographic record

VenueScience Advances · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsMcGill University
Fundersnot available
KeywordsIce sheetPost-glacial reboundGeologySea levelAntarctic ice sheetFuture sea levelOceanographyIce-sheet modelSea iceClimate changeGlacial periodGlobal warmingClimatologyArctic ice packAntarctic sea iceCryosphereGeomorphology

Abstract

fetched live from OpenAlex

The response of the Antarctic Ice Sheet (AIS) to climate change is the largest uncertainty in projecting future sea level. The impact of three-dimensional (3D) Earth structure on the AIS and future global sea levels is assessed here by coupling a global glacial isostatic adjustment model incorporating 3D Earth structure to a dynamic ice-sheet model. We show that including 3D viscous effects produces rapid uplift in marine sectors and reduces projected ice loss for low greenhouse gas emission scenarios, lowering Antarctica's contribution to global sea level in the coming centuries by up to ~40%. Under high-emission scenarios, ice retreat outpaces uplift, and sea-level rise is amplified by water expulsion from Antarctic marine areas.

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)0.003
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.013
GPT teacher head0.279
Teacher spread0.266 · 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

Citations23
Published2024
Admission routes1
Has abstractyes

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