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Record W4415365681 · doi:10.5194/tc-19-4611-2025

Review article: AntArchitecture – building an age–depth model from Antarctica's radiostratigraphy to explore ice-sheet evolution

2025· article· en· W4415365681 on OpenAlexafffund
Robert G. Bingham, Julien A. Bodart, Marie G. P. Cavitte, Ailsa Chung, Rebecca J. Sanderson, Johannes Sutter, Olaf Eisen, Nanna B. Karlsson, Joseph A. MacGregor, Neil Ross, D. A. Young, David W. Ashmore, Andreas Born, Winnie Chu, Xiangbin Cui, Reinhard Drews, Steven Franke, Vikram Goel, John W. Goodge, A. Clara J. Henry, Antoine Hermant, Benjamin Hills, Nicholas Holschuh, Michelle Koutnik, Gwendolyn J.‐M. C. Leysinger Vieli, Emma MacKie, Elisa Mantelli, Carlos Martín, Felix Ng, Falk M. Oraschewski, Felipe Napoleoni, Frédéric Parrenin, Sergey V. Popov, Therese Rieckh, Rebecca Schlegel, Dustin M. Schroeder, Martín J. Siegert, Xueyuan Tang, Thomas O. Teisberg, Kate Winter, Shuai Yan, Harry Davis, Christine F. Dow, T. J. Fudge, Tom A. Jordan, Bernd Kulessa, Kenichi Matsuoka, Clara J. Nyqvist, Maryam Rahnemoonfar, Matthew R. Siegfried, Shivangini Singh, Vjeran Višnjević, Rodrigo Zamora, Alexandra Zuhr

Bibliographic record

Venue˜The œcryosphere · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Waterloo
FundersHorizon 2020Natural Sciences and Engineering Research Council of CanadaNorges ForskningsrådNational Natural Science Foundation of ChinaDeutsche ForschungsgemeinschaftSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungEuropean Research CouncilNational Science Foundation
KeywordsVolcanoIce sheetProxy (statistics)Geologic recordArchitectureIce coreLead (geology)Geothermal gradient

Abstract

fetched live from OpenAlex

Abstract. Radio-echo sounding (RES) has revealed an internal architecture within both the West and East Antarctic ice sheets that records their depositional, deformational and melting histories. Crucially, RES-imaged internal-reflecting horizons, tied to ice-core age–depth profiles, can be treated as isochrones that record the age–depth structure across the Antarctic ice sheets. These enable the reconstruction of past climate and ice dynamical processes on large scales, which are complementary to but more spatially extensive than commonly used proxy records (e.g. former ice limits constrained by cosmogenic dating or offshore sediment sequences) around Antarctica. We review the progress towards building a pan-Antarctic age–depth model from these data by first introducing the relevant RES datasets that have been acquired across Antarctica over the last 6 decades (focussing specifically on those that detected internal-reflecting horizons) and outlining the processing steps typically undertaken to visualise, trace and date (by intersection with ice cores or modelling) the RES-imaged isochrones. We summarise the scientific applications for which Antarctica's internal architecture has been used to date and present a pathway to expanding Antarctic radiostratigraphy across the continent to provide a benchmark for a wider range of investigations: (1) identification of optimal sites for retrieving new ice-core palaeoclimate records targeting different periods; (2) reconstruction of surface mass balance on millennial or historical timescales; (3) estimation of basal melting and geothermal heat flux from radiostratigraphy and comprehensive mapping of basal-ice units to complement inferences from other geophysical and geological methods; (4) advancement of the knowledge of volcanic activity and fallout across Antarctica; and (5) refinement of numerical models that leverage radiostratigraphy to tune time-varying accumulation, basal melting and ice flow, firstly to reconstruct past behaviour and then to reduce uncertainties in projecting future ice-sheet behaviour.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.034
GPT teacher head0.269
Teacher spread0.235 · 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

Citations9
Published2025
Admission routes2
Has abstractyes

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