Tomography of core-mantle boundary and lowermost mantle coupled by geodynamics
Bibliographic record
Abstract
We propose an innovative approach to mapping CMB topography from seismic P-wave traveltime inversions: instead of treating mantle velocity and CMB topography as independent parameters, as has been done so far, we account for their coupling by mantle flow, as formulated by Forte & Peltier. This approach rests on the assumption that P data are sufficiently sensitive to thermal heterogeneity, and that compositional heterogeneity, albeit important in localized regions of the mantle (e.g. within the D″ region), is not sufficiently strong to govern the pattern of mantle-wide convection and hence the CMB topography. The resulting tomographic maps of CMB topography are physically sound, and they resolve the known discrepancy between images obtained from classic tomography on the basis of core-reflected and core-refracted seismic phases. Since the coefficients of mantle velocity structure are the only free parameters of the inversion, this joint tomography–geodynamics approach reduces the number of parameters; nevertheless the corresponding mantle models fit the seismic data as well as the purely seismic ones.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".