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Record W2100488177 · doi:10.1029/2006jb004850

On the origin and significance of subadiabatic temperature gradients in the mantle

2007· article· en· W2100488177 on OpenAlexaff
G. Sinha, S. L. Butler

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsAdvectionInternal heatingMantle (geology)GeologyConvectionMechanicsMantle convectionEnergy balanceGeothermal gradientGeophysicsTemperature gradientInternal energyThermodynamicsPhysicsMeteorologySubduction

Abstract

fetched live from OpenAlex

It is well established that the temperature gradients in the interiors of internally heated mantle convection models are subadiabatic. The subadiabatic gradients have been explained as arising because of a balance between vertical advection and internal heating; however, a detailed analysis of the energy balance in the subadiabatic regions has not been undertaken. In this paper, we examine in detail the energy balance in a suite of simple, two‐dimensional convection calculations with mixed internal and basal heating, depth‐dependent viscosity, and continents. We find that there are three causes of subadiabatic gradients. One is the above mentioned balance, which becomes significant when the ratio of internal heating to total surface heat flow is large. The second mechanism involves the growth of the “overshoot” of the geotherm near the lower boundary where the dominant balance is between vertical and horizontal advection. The latter mechanism is significant even in relatively weakly internally heated calculations. For time‐dependent calculations, we find that local secular cooling can be a dominant term in the energy equation and can lead to subadiabaticity. However, it does not show its signature on the shape of the time‐averaged geotherm. We also compare the basal heat flow with parameterized calculations based on the temperature drop at the core‐mantle boundary, calculated both with and without taking the subadiabatic gradient into account, and we find a significantly improved fit with its inclusion.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.028
GPT teacher head0.296
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations23
Published2007
Admission routes1
Has abstractyes

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