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Record W4381611078 · doi:10.1017/qua.2023.30

Massive ground ice of glacial meltwater origin in raised marine-deltaic sediments, Fosheim Peninsula, high Arctic Canada

2023· article· en· W4381611078 on OpenAlexafffundabout
Cameron Roy, Kethra Campbell-Heaton, Denis Lacelle, Wayne H. Pollard

Bibliographic record

VenueQuaternary Research · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of OttawaMcGill University
FundersEurostarsNatural Sciences and Engineering Research Council of Canada
KeywordsGeologyMeltwaterGlacial periodOceanographySea iceArcticArctic ice packIce shelfCryosphereGeomorphology

Abstract

fetched live from OpenAlex

Abstract In the Canadian high Arctic, tabular massive ground ice is found extensively throughout the Eureka Sound Lowlands (ESL). This study evaluates the development of tabular massive ice in raised marine-deltaic sediments of the ESL based on new cryostratigraphic data from sites found between the coastline and the Holocene marine limit. At all sites, massive ice is found below laminated fine-grained marine sediments, and the upper contact between the ice and the overlying marine sediments is conformable and gradational. The concentration of major ions in the massive ice is orders of magnitude higher than expected for glacial ice, but Na/Cl molar ratios vary following elevation: the higher-elevation site has ratios similar to glacial ice, but sites at lower elevations have ratios closer to seawater. The δ 18 O values of the ice indicate that the main source of water is glacial meltwater but the δD-δ 18 O regression slope values suggest that the ice formed in an open system while receiving an influx that had a substantially different isotopic signature than the initial reservoir. The development of massive ice in the marine-deltaic sediments involves glacial meltwater recharging an aquifer beneath the Holocene marine sediments with a contribution of 1–10% of seawater.

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 score0.040
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0190.001

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 head0.096
GPT teacher head0.326
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 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

Citations3
Published2023
Admission routes3
Has abstractyes

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