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Record W7052739594

Seasonal to interannual variability on the southeast Greenland shelf: a study focused on the Sermilik area

2020· dissertation· en· W7052739594 on OpenAlexaboutno aff

Bibliographic record

VenueARCA (Università Ca' Foscari Venezia) · 2020
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsBathymetryFjordGlacierOcean currentBoundary currentCurrent (fluid)Glacial periodWater massInflowContinental shelf
DOInot available

Abstract

fetched live from OpenAlex

The main objective of this thesis is to analyze the water mass variability and the circulation of the East Greenland boundary current system on the SE continental shelf and to properly represent the shelf/fjord exchange and fjord dynamics. Since the relative partitioning of the water masses composing the East Greenland Coastal Current (EGCC) changes both seasonally and inter-annually, a more complete understanding of this variability is important for (I) evaluating the amount of heat entering the glacial fjords and the melting of Greenland's outlet glaciers and (II) investigating the amount of freshwater the EGCC carry, influencing the stratification of the adjacent Labrador Sea, and in turn the deep convection and the strength of the Atlantic Meridional Overturning Circulation. Regarding the variability and evolution of the East Greenland boundary current system, the eddying GLOB16 configuration (with horizontal resolution of ~4 km in the region of interest) based on NEMO ocean model is used. On the other hand, to investigate the ocean dynamics within a fjord, a frontier-resolution configuration (with horizontal resolution of ~1 km in the region of interest) is employed in order to better resolve the ocean circulation inside the fjord and its interplay with the “open ocean” dynamics. Considering that the bathymetry plays a key role in regulating the AW inflow from the shelf and its circulation within a fjord, a new regional bathymetry product, BedMachine, is used to choose a more accurate input for the High-RES configuration, allowing a robust representation of the 3D fjord geometry and consequently the processes within.

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 score0.047
Threshold uncertainty score0.094

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 studies0.0000.000
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 head0.021
GPT teacher head0.248
Teacher spread0.227 · 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
Published2020
Admission routes1
Has abstractyes

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