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Record W4404326039 · doi:10.1029/2024gl111364

Baffin Bay Ice Export and Production From Sentinel‐1, the RADARSAT Constellation Mission, and CryoSat‐2: 2016–2022

2024· article· en· W4404326039 on OpenAlexafffundabout
Stephen Howell, David G. Babb, Jack Landy, G. W. K. Moore, Thomas J. Ballinger, Kaitlin McNeil, Benoît Montpetit, Mike Brady

Bibliographic record

VenueGeophysical Research Letters · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of ManitobaUniversity of TorontoEnvironment and Climate Change Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConstellationBayGeologyProduction (economics)Remote sensingOceanographyEnvironmental scienceAstronomyPhysics

Abstract

fetched live from OpenAlex

Abstract Baffin Bay is located between Greenland and several islands of the Canadian Arctic, providing a conduit for the downstream transport of ice and freshwater to the North Atlantic via Davis Strait. Using satellite observations from Sentinel‐1, the RADARSAT Constellation Mission, and CryoSat‐2, we estimated the sea ice export through Davis Strait and winter ice production in Baffin Bay from 2016 to 2022. The average annual ice export for this 6‐year period was 981 ± 193 × 10 3 km 2 for area 816 ± 130 km 3 for volume, and 653 ± 130 km 3 for solid freshwater, all of which are considerably higher than previously reported estimates. The average winter ice area production upstream of Davis Strait was 758 × 10 3 km 2 and the volume production was 589 km 3 indicating that more than 80% of the ice exported out of Baffin Bay was produced locally. Compared to Fram Strait, sea ice fluxes through Davis Strait represent ∼59% of the volume and ∼111% of the area.

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 score0.637
Threshold uncertainty score0.721

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.021
GPT teacher head0.266
Teacher spread0.244 · 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

Citations2
Published2024
Admission routes3
Has abstractyes

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