MétaCan
Menu
Back to cohort
Record W6963136219 · doi:10.18739/a24b2x68b

Near-surface permafrost studies near Bethel and remotely sensing ice wedge networks across the Yukon Kuskokwim Delta, Alaska 2025

2025· dataset· en· W6963136219 on OpenAlexaboutno aff

Bibliographic record

VenueCalifornia Digital Library · 2025
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostIce wedgeTundraArcticTransectHoloceneCryosphereThermokarstArctic ice pack

Abstract

fetched live from OpenAlex

This dataset documents the occurrence, distribution, and characteristics of cryptic ice wedge networks in the Yukon-Kuskokwim Delta (YKD), Alaska. The dataset is derived from remote sensing analyses, field-based permafrost coring, ground-penetrating radar (GPR) surveys, and stable water isotope analyses. High-resolution aerial orthoimagery from 2018 enabled the identification of ~50 linear kilometers (km) of ice wedge trough networks within a 60 square kilometers (km²) study area near Bethel, Alaska, revealing ice wedge networks previously undocumented in the region. Fieldwork in 2023 and 2024 confirmed the presence of ice wedges up to 1.5 meter (m) wide and 2.5 m tall, with wedge tops averaging 0.9 m below the surface. GPR transects identified additional ice wedges beyond those visible in imagery, suggesting that remote sensing analyses may underestimate their true abundance. Coring of polygon centers revealed a suite of late-Quaternary deposits, including early Holocene peat, ice-rich late-Pleistocene permafrost (reworked Yedoma), charcoal layers indicating past tundra fires, and the Aniakchak CFE II tephra (~3,600 calendar years before present [cal yrs BP]). Stable water isotope analyses of wedge ice (mean δ¹⁸O = -15.7 ‰, δ²H = -113.1 ‰) indicate relatively enriched values compared to other Holocene ice wedges in Alaska, reflecting the region's warm maritime climate influence. Expanding the mapping analysis across the YKD using very high-resolution satellite imagery, we found that 95 % of observed ice wedge networks occur at elevations between 4 and 80 meters above sea level (m asl), predominantly within tundra vegetation classes. These areas, covering ~32 % of the YKD tundra region, may contain additional ice wedges, peat deposits, and relict Yedoma. This dataset provides a new framework for understanding the spatial distribution and environmental controls on ice wedge development in warm permafrost regions, with implications for permafrost resilience, climate change vulnerability, and land use planning in the YKD.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.040
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.026
GPT teacher head0.256
Teacher spread0.230 · 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 designNot applicable
Domainnot available
GenreDataset

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

Explore more

Same venueCalifornia Digital LibrarySame topicClimate change and permafrostFrench-language works237,207