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Record W2015712568 · doi:10.1016/j.yqres.2007.05.003

Molar gas ratios of air entrapped in ice: A new tool to determine the origin of relict massive ground ice bodies in permafrost

2007· article· en· W2015712568 on OpenAlexaffabout
Raphaelle Cardyn, Ian D. Clark, Denis Lacelle, Bernard Lauriol, Christian Zdanowicz, Fabrice Calmels

Bibliographic record

VenueQuaternary Research · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsGeological Survey of CanadaNatural Resources CanadaUniversité LavalUniversity of Ottawa
Fundersnot available
KeywordsGeologyPermafrostCryosphereArctic ice packGlacierIce streamIce divideSnowAtmospheric sciencesGeomorphologyArcticSea iceClimatologyOceanography

Abstract

fetched live from OpenAlex

Abstract The molar ratios of atmospheric gases change during dissolution in water due to differences in their relative solubilities. We exploited this characteristic to develop a tool to clarify the origin of ice formations in permafrost regions. Extracted from ice, molar gas ratios can distinguish buried glacier ice from intrasedimental ground ice formed by freezing groundwaters. An extraction line was built to isolate gases from ice by melting and trapping with liquid He, followed by analysis of N 2 , O 2, , Ar, 18 O O2 and 15 N N2 , by continuous flow mass spectrometry. The method was tested using glacier ice, aufeis ice (river icing) and intrasedimental ground ice from sites in the Canadian Arctic. O 2 /Ar and N 2 /Ar ratios clearly distinguish between atmospheric gas in glacial ice and gases from intrasedimental ground ice, which are exsolved from freezing water. δ 15 N N2 and δ 18 O O2 in glacier ice, aufeis ice and intrasedimental ground ice do not show clear distinguishing trends as they are affected by various physical processes during formation such as gravitational settling, excess air addition, mixing with snow pack, and respiration.

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)0.002
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 score0.006
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.086
GPT teacher head0.339
Teacher spread0.254 · 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

Citations33
Published2007
Admission routes2
Has abstractyes

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