Tomography of core-mantle boundary and lowermost mantle coupled by geodynamics: joint models of shear and compressional velocity
Bibliographic record
Abstract
We conduct joint tomographic inversions of P and S travel time observations to obtain models of delta v_P and delta v_S in the entire mantle. We adopt a recently published method which takes into account the geodynamic coupling between mantle heterogeneity and core-mantle boundary (CMB) topography by viscous flow, where sensitivity of the seismic travel times to the CMB is accounted for implicitly in the inversion (i.e. the CMB topography is not explicitly inverted for). The seismic maps of the Earth's mantle and CMB topography that we derive can explain the inverted seismic data while being physically consistent with each other. The approach involved scaling P-wave velocity (more sensitive to the CMB) to density anomalies, in the assumption that mantle heterogeneity has a purely thermal origin, so that velocity and density heterogeneity are proportional to one another. On the other hand, it has sometimes been suggested that S-wave velocity might be more directly sensitive to temperature, while P heterogeneity is more strongly influenced by chemical composition. In the present study, we use only S-, and not P-velocity, to estimate density heterogeneity through linear scaling, and hence the sensitivity of core-reflected P phases to mantle structure. Regardless of whether density is more closely related to P- or S-velocity, we think it is worthwhile to explore both scaling approaches in our efforts to explain seismic data. The similarity of the results presented in this study to those obtained by scaling P-velocity to density suggests that compositional anomaly has a limited impact on viscous flow in the deep mantle.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".