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Record W2147437185 · doi:10.4319/lo.2013.58.3.0803

Remote climate forcing of decadal‐scale regime shifts in Northwest Atlantic shelf ecosystems

2013· article· en· W2147437185 on OpenAlexaff
Charles H. Greene, Erin Meyer‐Gutbrod, Bruce C. Monger, Louise P. McGarry, Andrew J. Pershing, Igor M. Belkin, Paula Fratantoni, David Mountain, Robert S. Pickart, Andrey Proshutinsky, Rubao Ji, James J. Bisagni, Sirpa Häkkinen, Dale B. Haidvogel, Jia Wang, Erica Head, Peter Smith, Philip C. Reid, Alessandra Conversi

Bibliographic record

VenueLimnology and Oceanography · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
FundersUniversity of WashingtonNational Science Foundation
KeywordsForcing (mathematics)OceanographyEnvironmental scienceEcosystemMarine ecosystemClimatologyClimate changeStructural basinGeologyEcology

Abstract

fetched live from OpenAlex

Decadal‐scale regime shifts in Northwest Atlantic shelf ecosystems can be remotely forced by climate‐associated atmosphere‐ocean interactions in the North Atlantic and Arctic Ocean Basins. This remote climate forcing is mediated primarily by basin‐ and hemispheric‐scale changes in ocean circulation. We review and synthesize results from process‐oriented field studies and retrospective analyses of time‐series data to document the linkages between climate, ocean circulation, and ecosystem dynamics. Bottom‐up forcing associated with climate plays a prominent role in the dynamics of these ecosystems, comparable in importance to that of top‐down forcing associated with commercial fishing. A broad perspective, one encompassing the effects of basin‐ and hemispheric‐scale climate processes on marine ecosystems, will be critical to the sustainable management of marine living resources in the Northwest Atlantic.

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)0.001
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.006
GPT teacher head0.207
Teacher spread0.201 · 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

Citations113
Published2013
Admission routes1
Has abstractyes

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