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Record W4404209205 · doi:10.1029/2024jc021195

Nutrient‐Rich Winter Water Formation on the Beaufort Shelf, Arctic Ocean

2024· article· en· W4404209205 on OpenAlexaboutno aff
Yanxin Wang, Peigen Lin, Robert S. Pickart

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaFundamental Research Funds for the Central UniversitiesNational Oceanic and Atmospheric AdministrationNational Science Foundation
KeywordsBeaufort seaOceanographyBeaufort scaleArcticThe arcticEnvironmental scienceGeology

Abstract

fetched live from OpenAlex

Abstract Newly ventilated winter water (NVWW) is a cold, salty, nutrient‐rich water mass that is critical for supporting the ecosystem of the western Arctic Ocean and for ventilating the halocline in the Canada Basin. While the formation of NVWW is well‐documented on the Chukchi shelf, there remain fundamental questions regarding its formation on the western Beaufort shelf. In this study, we use hydrographic data from two late‐fall cruises in 2018 and 2022 to investigate the roles of sea ice production and wind‐driven upwelling in the formation of NVWW and the implications for the nutrient content of the water. For each of the shipboard transects, we apply proxies for the extent of the winter water formation and the strength of the associated upwelling, respectively. It is demonstrated that the NVWW attains higher levels of nitrate due to two factors: (a) more active formation of the water associated with enhanced sea ice production and (b) more extensive upwelling of water high in nutrients from the basin to the shelf following an easterly wind event. The latter process would be less common on the wide Chukchi shelf. These findings have significant implications for the regional primary production.

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 score0.482
Threshold uncertainty score0.958

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 science0.0000.000
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 head0.028
GPT teacher head0.283
Teacher spread0.255 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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