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Record W4243958293 · doi:10.1002/essoar.10506615.1

Winter Dynamics in an Epishelf Lake: Quantitative Mixing Estimates and Ice Shelf Basal Channel Considerations

2021· preprint· en· W4243958293 on OpenAlexaffabout
Jérémie Bonneau, B. Laval, Derek Mueller, Alexander L. Forrest, Drew M. Friedrichs, Andrew K. Hamilton

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of AlbertaCarleton UniversityUniversity of British Columbia
Fundersnot available
KeywordsPreprintChannel (broadcasting)World Wide WebComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Milne Ice Shelf is located at the mouth of Milne Fiord (82.6$^\circ$N, 81.0$^\circ$W), on Ellesmere Island, Nunavut. This floating ice feature is attached to both sides of the fjord. During the melt season, the ice shelf acts as a dam preventing surface runoff from flowing freely to the ocean. This results in a permanent layer of freshwater that “floats” on top of the seawater of the fjord, commonly known as an epishelf lake. The winter data from a mooring installed in Milne Fiord epishelf lake (2011-2019) is analysed in the framework of a one-dimensional model in order to 1) study mixing in the upper water column and 2) infer the characteristics of a basal channel in the ice shelf. The results show that vertical mixing rates are higher in the epishelf lake than in the seawater below. Estimation of the Richardson number using a geostrophic balance approach reveals that enhanced mixing in the epishelf lake is associated with horizontal temperature gradients. Moreover, the analysis suggests that the epishelf lake water reaching the ocean travels through a single basal channel in the ice shelf. The model did not detect significant variation in outflow characteristics over the eight years of study, implying that the area of the basal channel is in ice mass balance.

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)0.001
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 score0.081
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.045
GPT teacher head0.273
Teacher spread0.228 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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