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Record W2371630504 · doi:10.1017/jog.2016.62

Cryoconite hole connectivity on the Wright Lower Glacier, McMurdo Dry Valleys, Antarctica

2016· article· en· W2371630504 on OpenAlexafffund
Shelley MacDonell, Martin Sharp, Sean J. Fitzsimons

Bibliographic record

VenueJournal of Glaciology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaNatural Resources CanadaAntarctica New ZealandUniversity of Otago
KeywordsGlacierGeologyBiotaSpatial variabilityGeomorphologyPhysical geographyOceanographyEcologyGeography

Abstract

fetched live from OpenAlex

ABSTRACT Cryoconite holes can be important sources and stores of water and nutrients on cold and polythermal glaciers, and they provide a habitat for various forms of biota. Understanding the hydrological connectivity of cryoconite holes may be the key to understanding the transport of nutrients and biological material to the proglacial areas of such glaciers. This paper aims to characterize and explain spatial variability in the connectivity of ice-lidded cryoconite holes on a small, piedmont glacier in the McMurdo Dry Valleys through geochemical analysis of cryoconite hole waters. Solute concentrations in both surface and near-surface ice and cryoconite holes, vary greatly along the glacier centerline, and all sample types displayed similar spatial patterns of variability. Using chloride as a tracer, we estimated variations in cryoconite hole connectivity along the glacier centerline. We found that a previously used mass transfer method did not provide reliable estimates of the time period for which cryoconite hole waters had been isolated from the atmosphere. We attribute this to spatial variability in both the chloride content of the surface ice and surface ablation rates. The approach may, however, be used to qualitatively characterize spatial variations in the hydrological connectivity of the cryoconite holes. These results also suggest that ice-lidded cryoconite holes are never truly isolated from the near-surface drainage system.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score0.439

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.015
GPT teacher head0.249
Teacher spread0.235 · 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

Citations13
Published2016
Admission routes2
Has abstractyes

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