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Record W3131456976 · doi:10.1017/qua.2020.126

Holocene ice wedge formation in the Eureka Sound Lowlands, high Arctic Canada

2021· article· en· W3131456976 on OpenAlexaffabout
Kethra Campbell-Heaton, Denis Lacelle, David Fisher, Wayne H. Pollard

Bibliographic record

VenueQuaternary Research · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsMcGill UniversityUniversity of Ottawa
Fundersnot available
KeywordsPermafrostGeologyIce wedgeHoloceneSnowArcticSea iceSnowmeltOceanographyArctic ice packPeatGeomorphologyPeninsulaPhysical geography

Abstract

fetched live from OpenAlex

Abstract Ice wedges are ubiquitous periglacial features in permafrost terrain. This study investigates the timing of ice wedge formation in the Fosheim Peninsula (Ellesmere and Axel Heiberg Islands). In this region, ice wedge polygons occupy ~50% of the landscape, the majority occurring below the marine limit in the Eureka Sound Lowlands. Numerical simulations suggest that ice wedges may crack to depths of 2.7–3.6 m following a rapid cooling of the ground over mean winter surface temperatures of −18°C to −38°C, corresponding to the depth of ice wedges in the region. The dissolved organic carbon (DOC)/Cl molar ratios suggest that the DOC in the ice wedges is sourced from snowmelt and not from leaching of the active layer. Based on 32 14 C DOC measurements from 15 ice wedges, the wedges were likely developing between 9000–2500 cal yr BP. This interval also corresponds to the period of peat accumulation in the region, a proxy of increased moisture. Considering that winter air temperatures remained favorable for ice wedge growth throughout the Holocene, the timing of ice wedge formation reflects changes in snowfall. Overall, this study provides the first reconstruction of ice wedge formation from a high Arctic polar desert environment.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.121
GPT teacher head0.321
Teacher spread0.199 · 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 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

Citations10
Published2021
Admission routes2
Has abstractyes

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