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Record W1976023005 · doi:10.5194/os-10-127-2014

The instability of diffusive convection and its implication for the thermohaline staircases in the deep Arctic Ocean

2014· article· en· W1976023005 on OpenAlexfundno aff
Sheng‐Qi Zhou, Ling Qu, Yuan‐Zheng Lu, Xu Song

Bibliographic record

VenueOcean science · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersDivision of Ocean SciencesFisheries and Oceans CanadaWoods Hole Oceanographic InstitutionChinese Academy of SciencesNational Science Foundation
KeywordsConvectionStratification (seeds)Thermohaline circulationInstabilityGeologyArcticDeep convectionRayleigh numberThe arcticGeophysicsConvective instabilityClimatologyOceanographyMechanicsNatural convectionPhysics

Abstract

fetched live from OpenAlex

Abstract. In the present study, the classical description of diffusive convection is updated to interpret the instability of diffusive interfaces and the dynamical evolution of the bottom layer in the deep Arctic Ocean. In the new consideration of convective instability, both the background salinity stratification and rotation are involved. The critical Rayleigh number of diffusive convection is found to vary from 103 to 1011 in the deep Arctic Ocean as well as in other oceans and lakes. In such a wide range of conditions, the interface-induced thermal Rayleigh number is shown to be consistent with the critical Rayleigh number of diffusive convection. In most regions, background salinity stratification is found to be the main hindrance to the occurrence of convecting layers. With the new parameterization, it is predicted that the maximum thickness of the bottom layer is 1051 m in the deep Arctic Ocean, which is close to the observed value of 929 m. The evolution time of the bottom layer is predicted to be ~ 100 yr, which is on the same order as that based on 14C isolation age estimation.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.271
Teacher spread0.251 · 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 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

Citations7
Published2014
Admission routes1
Has abstractyes

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