The role of thermal effect on mantle seismic anomalies under Laurentia and Fennoscandia from observations of Glacial Isostatic Adjustment
Bibliographic record
Abstract
An outstanding issue in the study of seismic tomography is the role of thermal versus non-thermal (e.g. compositional, partial melting) contribution to seismic velocity anomalies. Here we use observations of glacial isostatic adjustment (GIA), including global sea levels, observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission and GPS crustal uplift rates to show that thermal effect increases from about 65 per cent in the upper mantle to about 75 per cent in the shallow part of the lower mantle and to about 100 per cent in the deep lower mantle above the D′′ layer. This is consistent with temperature excess in the lower mantle from high core heating. However, the uncertainty increases from ∼10 per cent in the upper mantle to ∼40 per cent in the shallow lower mantle and is not well constrained in the deep lower mantle. The implication of large thermal contribution is that hot buoyant plumes can cause large viscosity reduction which may allow convection motion to occur easier even if the viscosity in the lower mantle is high.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".