Bibliographic record
Abstract
Abstract We have attempted to infer details of the viscosity structure in the top 1000 km of the mantle from the geoid and tomographic structure beneath the oceans. In order to eliminate the gravity signal from problematic masses located below the subduction zones and the continents, we have considered only the intermediate degrees of the oceanic geoid (l = 12–25). A genetic algorithm has been used to determine the family of viscosity models which give the best correlation with the observed geoid. Our inversion clearly identifies the asthenosphere just below the lithosphere and also confirms the viscosity increase in the lower mantle predicted by previous inferences, but suggests that the main viscosity jump occurs at a depth of about 1000 km and not at the usually stated 660-km boundary. Somewhere in the depth range of 400–1000 km, a low viscosity zone may exist where the viscosity decreases to a value comparable with the asthenosphere. Existence of such a low viscosity zone is supported by recent analysis of deep mantle anisotropy which favours a flow pattern with a strong horizontal component in the top part of the lower mantle. Unfortunately, the resolution of the inversion as well as the quality of recent seismic tomographic models are not sufficient to localize the depth and to come up with a higher accuracy for the viscosity of this low viscosity channel.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.989 | 0.992 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".