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Record W2279689130 · doi:10.1002/2015pa002920

On the reconstruction of ocean circulation and climate based on the “Gardar Drift”

2016· article· en· W2279689130 on OpenAlexaboutno aff
Helene R. Langehaug, Tor L. Mjell, Odd Helge Otterå, Tor Eldevik, Ulysses S. Ninnemann, H. F. Kleiven

Bibliographic record

VenuePaleoceanography · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersBjerknessenteret for klimaforskning, Universitetet i BergenNorges ForskningsrådComer Science and Education Foundation
KeywordsGeologyShetlandOceanographyBottom waterClimatologySedimentChannel (broadcasting)Paleontology

Abstract

fetched live from OpenAlex

Abstract Sediment‐based reconstructions of bottom water velocity at the Gardar Drift are commonly interpreted to reflect changes in the eastern Nordic Seas overflows. Here we investigate the relationship between changes in the water that overflows through the Faroe Shetland Channel and downstream bottom velocity at the location of the Gardar Drift as represented in a 500 year long simulation with the Bergen Climate Model. We identify a region in our simulation proximal to the geographical location of the northern Gardar Drift where 76% of the variance in bottom velocity can be explained by changes in the volume transport and density of the Faroe Shetland Channel overflow. By contrast, Labrador Sea Water changes do not appear to play a significant role in the bottom flow over the Gardar Drift. Our findings support the assumption in the paleo literature that reconstructions of bottom water velocity at the Gardar Drift reflect past changes in the eastern Nordic Seas overflows. However, our results suggest that velocity changes downstream are not a simple metric for the strength of the overflow, rather overflow density plays the largest role.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.014
GPT teacher head0.205
Teacher spread0.191 · 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

Citations9
Published2016
Admission routes1
Has abstractyes

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