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Record W2104259026 · doi:10.1029/2006gl029209

Impact of diapycnal mixing on the saturation state of argon in the subtropical North Pacific

2007· article· en· W2104259026 on OpenAlexaff
Takamitsu Ito, Curtis Deutsch, Steven Emerson, Roberta C. Hamme

Bibliographic record

VenueGeophysical Research Letters · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsUniversity of Victoria
FundersJoint Institute for the Study of the Atmosphere and OceanUniversity of WashingtonNational Oceanic and Atmospheric AdministrationNational Science Foundation
KeywordsThermoclineTransectGeologyTRACERMixing (physics)Ocean gyreOceanographyAtmospheric sciencesEnvironmental scienceSubtropicsPhysics

Abstract

fetched live from OpenAlex

Diapycnal mixing plays an important role in both physical and biogeochemical processes in the oceans, yet the rate of tracer mixing has not been adequately quantified. A theoretical analysis predicts that diapycnal mixing should raise the saturation state of noble gases in the thermocline, at a rate proportional to diapycnal diffusivity. We apply this theory to existing measurements of argon in the ventilated thermocline, where the increase in the saturation state should be proportional to the integrated effect of diapycnal mixing. Combining argon observations from time‐series stations in the North Pacific with freon ventilation age, we tentatively estimate the regional diapycnal diffusivity at 0.35 ± 0.21 10 −4 m 2 s −1 . Major sources of uncertainty include spatial and temporal variability and sparse sampling. These uncertainties could be significantly reduced using measurements of several noble gases in a transect from the isopycnal outcrop to the interior gyre.

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)0.000
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 score0.034
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.027
GPT teacher head0.287
Teacher spread0.260 · 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

Citations26
Published2007
Admission routes1
Has abstractyes

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