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Record W4221017702 · doi:10.5194/egusphere-egu22-9395

The role of Irminger Rings for biogeochemical tracer advection in the Labrador Sea.

2022· preprint· en· W4221017702 on OpenAlexaffabout
Ahmad Fehmi Dilmahamod, Katja Fennel, Arnaud Laurent, Johannes Karstensen

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBiogeochemical cycleOceanographyEddyAdvectionBoundary currentOcean currentGeologyConvectionWater columnStratification (seeds)Convective mixingGeographyChemistryMeteorology

Abstract

fetched live from OpenAlex

The Labrador Sea is one of two major sites of the subpolar North Atlantic where deep convection occurs in wintertime as the ambient stratification is weakened through surface cooling and the water column homogenized to up to 2000 m depth. Deep convection has important biogeochemical implications, for example, the ventilation of the deep ocean through the formation of Labrador Sea Water, when convective mixing brings deep-water, undersaturated in oxygen, in contact with the atmosphere. Oceanic eddies in the Labrador Sea, in particular Irminger Rings, are known to transport heat and freshwater from the boundary current towards the central basin. This process regulates the strength of convection by influencing the preconditioning and restratification processes, hence modulating the production of Labrador Sea Water. However, the impact of these eddies on lateral biogeochemical fluxes between the coastal and open Labrador Sea, including the regions where deep convection is most pronounced, remains elusive. In this study, a high-resolution (1/12°) coupled biogeochemical-physical model of the northwest North Atlantic is employed to investigate the role of these eddies for lateral transport of biogeochemical constituents in the three distinct regions: eastern and western boundary and the central Labrador Sea. Oxygen, nutrient, and carbon budgets for these regions will be presented with an emphasis on horizontal and vertical transports, and mean and eddy-driven advection. The results of the biogeochemical budgets will be compared with those from the heat and freshwater budgets.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.020
GPT teacher head0.223
Teacher spread0.204 · 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 routes2
Has abstractyes

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