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Record W2056863308 · doi:10.1088/2041-8205/727/1/l8

THERMOHALINE MIXING: DOES IT REALLY GOVERN THE ATMOSPHERIC CHEMICAL COMPOSITION OF LOW-MASS RED GIANTS?

2010· article· en· W2056863308 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Astrophysical Journal Letters · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsThermohaline circulationMixing (physics)AdvectionConvectionComplete mixingDiffusionPhysicsRed-giant branchConvective mixingMechanicsAtmospheric sciencesMass transferAstrophysicsGeologyThermodynamicsStarsClimatologyGlobular cluster

Abstract

fetched live from OpenAlex

First results of our 3D numerical simulations of thermohaline convection driven by 3He burning in a low-mass RGB star at the bump luminosity are presented. They confirm our previous conclusion that this convection has a mixing rate which is a factor of 50 lower than the observationally constrained rate of RGB extra-mixing. It is also shown that the large-scale instabilities of salt-fingering mean field (those of the Boussinesq and advection-diffusion equations averaged over length and time scales of many salt fingers), which have been observed to increase the rate of oceanic thermohaline mixing up to one order of magnitude, do not enhance the RGB thermohaline mixing. We speculate on possible alternative solutions of the problem of RGB extra-mixing, among which the most promising one that is related to thermohaline mixing is going to take advantage of the shifting of salt-finger spectrum towards larger diameters by toroidal magnetic field.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.004
GPT teacher head0.191
Teacher spread0.187 · 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