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Record W4408431741 · doi:10.5194/egusphere-egu25-12393

Proglacial Retrogressive Thaw Slumping, Svalbard

2025· preprint· en· W4408431741 on OpenAlexaff
Liam Carson, Brian J. Moorman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSlumpingGeologyGeomorphologyGeotechnical engineering

Abstract

fetched live from OpenAlex

The Arctic is currently experiencing warming at much higher rates when compared to the global average, which has led to rapid changes within the cryosphere, including glacial retreat and permafrost thaw. These climate-induced processes are transforming proglacial environments, with ice-cored moraine thaw driving rapid landscape evolution. Although topographical changes caused by thawing ice-cored moraines have been studied in the Arctic, there is a lack of ice-cored moraine studies in central Spitsbergen. In this study, we present Unmanned Aerial Vehicle (UAV)-derived models of two glacial forefields in central Spitsbergen, Scott Turnerbreen (STB) and Longyearbreen (LYB), where six aerial photogrammetric surveys were flown over the course of three weeks, providing a high temporal resolution for three specific Retrogressive Thaw Slumps (RTS) and the forefields themselves. Previous aerial imagery captured in 2018 and satellite imagery gathered from 2014 allow for a greater range of temporal frequencies. Furthermore, using Ground Penetrating Radar (GPR), sites that experienced movement, as observed from the aerial surveys, were tested to determine if the cause of movement could be directly correlated to the melting ground ice. STB saw a loss of 67350m3 since 2018, with one-third of that volume loss being attributed to the three RTSs observed in this study. Since 2018, the LYB has lost 115,252m3 in volume, almost double the amount observed in STB. This disparity in lost material is evident in the area of the visible RTSs occurring in both study sites, with the LYB being home to an RTS almost 3 times the size of the largest RTS observed in STB. By integrating surface and subsurface analyses, this study provides a comprehensive understanding of ice-cored moraine dynamics under climate change, highlighting implications for geomorphological stability, sediment release, and hydrological systems. These findings emphasize the urgent need for continued monitoring and predictive modelling to assess the persistence of such changes in these Arctic proglacial landscapes.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.044
GPT teacher head0.283
Teacher spread0.239 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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