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Record W4220690431 · doi:10.5194/egusphere-egu22-8941

North Water Polynya Sensitivity to Arctic Warming

2022· preprint· en· W4220690431 on OpenAlexaboutno aff
Rajan Patel, Patrick Ugrinow, Alexandra Jahn, Chris Wyburn-Powell

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBayEnvironmental scienceClimate changeClimatologyOceanographyGlobal warmingNutrientThe arcticArcticEcologyGeologyBiology

Abstract

fetched live from OpenAlex

The North Water Polynya (NOW) in northern Baffin Bay contains nutrient-rich waters which are essential to the biodiversity of the region and the native Inuit people. Over the observational period the size and duration of the NOW in spring has varied considerably, and recent studies suggest the NOW may fail to form in the future. Even small changes to the polynya have the potential to impact local ocean circulation and nutrient cycling. To assess the projected changes to the NOW, we look at CMIP5 large ensembles under multiple forcing scenarios. Initial results from CESM1 LE suggest that global temperatures greater than 2.5ºC above pre-industrial levels shift the peak polynya area from June to May. Work is ongoing to assess biogenic and physical impacts of such changes. Implications for climate change are that to avoid large changes to the NOW, warming should be limited. Additionally, the Polynya area fluctuates with time but decreases as a whole throughout the 21st century.

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 score0.195
Threshold uncertainty score0.387

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 communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.039
GPT teacher head0.329
Teacher spread0.290 · 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
Published2022
Admission routes1
Has abstractyes

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