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Record W4400416135 · doi:10.1139/as-2024-0003

Stable isotopes of landfast sea ice as a record of La Grande River under-ice plume dispersal

2024· article· en· W4400416135 on OpenAlexaffvenue
Aura Diaz, Zou Zou A. Kuzyk, Alessia Guzzi, Kaushik Gupta, Tim Papakyriakou, Jens K. Ehn

Bibliographic record

VenueArctic Science · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSea iceBiological dispersalOceanographyPlumeGeologyIce shelfAntarctic sea iceArctic ice packPhysical geographyCryosphereGeographyMeteorology

Abstract

fetched live from OpenAlex

Vertical profiles of salinity, and isotopic abundance ratios of hydrogen (δ 2 H) and oxygen (δ 18 O) of 18 landfast ice cores, collected along the northeast coast of James Bay in March 2019, and one ice core collected in Belcher Islands, were used to obtain the winter timeseries of the spatiotemporal evolution of the under-ice plume of La Grande River (LGR), the dominant river in the area. Variability in the isotopic composition and salinity of the ice cores indicated changes to the water source composition at the ice–water interface when the ice layers formed. The increased presence of river water beneath the ice during January–March was marked by more negative isotopic ratios in the lower portion of the ice as river discharge was increased for hydroelectric production. River water was the source of ∼43% of the ice in our ice core samples ( n = 320) with the interquartile range from 16% to 71%. The river water fractions incorporated into the ice indicate that LGR under-ice plume extended more than 75 km north and at least 30 km south of the river mouth for ∼3 months. These findings correspond well with more challenging to obtain hydrographic observations. End-of-winter ice core sampling and analysis for isotopic abundance has potential as a tool to monitor dispersal of LGR discharge into the ice-covered coastal 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 score0.228
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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