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Record W3209742744 · doi:10.5281/zenodo.1205509

Hysteresis and temporary resilience of the AMOC in an eddy-permitting GCM

2018· dataset· en· W3209742744 on OpenAlexaboutno aff
Laura Jackson, Richard Wood

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2018
Typedataset
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsGCM transcription factorsResilience (materials science)HysteresisLarge eddy simulationEnvironmental scienceGeologyPhysicsMeteorologyClimate changeGeneral Circulation ModelOceanographyCondensed matter physicsTurbulenceThermodynamics

Abstract

fetched live from OpenAlex

Data for reproducing figures in the publication "Hysteresis and temporary resilience of the AMOC in an eddy-permitting GCM". moc_26Nmax.nc - timeseries of AMOC strength (Sv) measured as the maximum at 26N. MLD_LSmax.nc - timeseries of maximum March mixed layer depth (m) in the Labrador Sea (53-65N,48-62W) MLD_area500.nc - area (m2) where March mixed layer depth in the N Atlantic > 500m dens_NATL.nc - density (kg/m3) averaged over full depth and 30N to the Bering Strait. Also contains density due to salinity (DS) and temperature (DT) changes only from the time hosing stops in each experiment sbudg_experiment.nc contains the salinity budget (1e6 PSU m3/s) for the volume covering full depth and from 30N to the Bering Strait. Components are dS/dt, surface fluxes, diffusion and advection. Also advection is geometrically broken into that from the throughflow, that from the gyre and that from the overturning For all time is in years. Experiments are defined the following way: control - preindustrial control with no added hosing hosH - run where hosing of strength H Sverdrups is applied (ie hos01 has 0.1 Sv) offH_T - run which starts after hosing H Sverdups has been applied for T years.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.012
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.027
GPT teacher head0.248
Teacher spread0.221 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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
Published2018
Admission routes1
Has abstractyes

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