MétaCan
Menu
Back to cohort
Record W1965871785 · doi:10.1080/03091920108203412

A steady-state coupled ocean-polynya flux model of the North Water, Baffin Bay

2001· article· en· W1965871785 on OpenAlexfundno aff
Nicholas R. T. Biggs, Andrew J. Willmott

Bibliographic record

VenueGeophysical & Astrophysical Fluid Dynamics · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersNatural Environment Research CouncilUniversity of Manitoba
KeywordsEntrainment (biomusicology)GeologyWind stressMass fluxSea iceDragBoundary layerSea ice growth processesSea ice thicknessArctic ice packAtmospheric sciencesClimatologyMechanicsPhysics

Abstract

fetched live from OpenAlex

Abstract A steady-state coupled wind-driven reduced-gravity polynya flux model is developed to study the maintenance of the North Water Polynya. The following features are incorporated into the coupled model: (i) arbitrary wind stress; (ii) entrainment of fluid into the upper active layer from the deep motionless layer; (iii) frazil ice trajectories determined from the free-drift ice momentum balance; (iv) the collection depth of frazil ice at the polynya edge is calculated using a parameterization in terms of the depth of frazil ice arriving at the edge and the normal component to the edge of the frazil ice velocity relative to the consolidated new ice velocity. Solutions are calculated for a range of values of the meridional mass flux across Nares Strait (the northern boundary of the domain), wind stress orientation, entrainment rates and the ice-water drag coefficient. The polynya edge is found to be insensitive to entrainment, in agreement with previous modeling studies. On the other hand, the polynya is extremely sensitive to the magnitude of the ice-water drag coefficient and the meridional mass transport across the northern boundary. Also included are two simulations of the North Water Polynya which incorporate forecasted wind stress data.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.184
Teacher spread0.177 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations12
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueGeophysical & Astrophysical Fluid DynamicsSame topicArctic and Antarctic ice dynamicsFrench-language works237,207