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Record W4313529138 · doi:10.1016/j.pocean.2022.102955

Review of oceanic mesoscale processes in the North Pacific: Physical and biogeochemical impacts

2023· article· en· W4313529138 on OpenAlexafffund
Hiromichi Ueno, Annalisa Bracco, John A. Barth, M. V. Budyansky, Daisuke Hasegawa, Sachihiko Itoh, Sung Yong Kim, Carol Ladd, Xiaopei Lin, Young‐Gyu Park, S. V. Prants, Tetjana Ross, Irina I. Rypina, Yoshikazu Sasai, О. О. Трусенкова, Е И Устинова, Yisen Zhong

Bibliographic record

VenueProgress In Oceanography · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsFisheries and Oceans Canada
FundersNOAA Pacific Marine Environmental LaboratoryKorea Institute of Marine Science and Technology promotionNorth Pacific Marine Science Organization
KeywordsBiogeochemical cycleMesoscale meteorologyOceanographyEddyMarine ecosystemEnvironmental scienceEcosystemClimatologyGeologyGeographyMeteorologyEcology

Abstract

fetched live from OpenAlex

Physical transport dynamics occurring at the ocean mesoscale (∼20 km – 200 km) largely determine the environment in which biogeochemical processes occur. As a result, understanding and modeling mesoscale transport is crucial for determining the physical modulations of the marine ecosystem. This review synthesizes current knowledge of mesoscale eddies and their impacts on the marine ecosystem across most of the North Pacific and its marginal Seas. The North Pacific domain north of 20°N is divided in four regions, and for each region known, unknowns and known-unknowns are summarized with a focus on physical properties, physical-biogeochemical interactions, and the impacts of climate variability and change on the eddy field and on the marine ecosystem.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations42
Published2023
Admission routes2
Has abstractyes

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