Mantle reflectivity structure beneath oceanic hotspots
Bibliographic record
Abstract
This study applies high-resolution Radon transform to a large set of SS precursors and explores the mantle reflectivity structure beneath 17 potentially ‘deep-rooted’ hotspots. The combined reduced time (τ) and ray parameter (p) information effectively constrains the depth, spatial distribution and sharpness of upper-/mid-mantle reflectors. The olivine to wadsleyite phase boundary is deeper than the ocean and global averages and produces a dominant τ–p domain signal. Laterally coherent observations of the deep 410-km seismic discontinuity, thin upper mantle transition zone and weak/absent 520-km reflector beneath hotspots make compelling arguments for large-scale, hot thermal anomalies in the top 400–600 km of the mantle. On the other hand, a relatively ‘flat’ and weak reflector at ∼653 km is inconsistent with ringwoodite to silicate perovskite + magnesiowüstite transformation at temperatures greater than 2000 K. The lack of a negative correlation between topography and temperature implies (1) average or below-average temperatures at 600–700 km depths or (2) high temperatures and a dominating majorite garnet to Ca perovskite phase transformation. The proper choice between these two scenarios will directly impact the origin and depth of mantle plumes beneath hotspots. We further identify lower-mantle reflectors at 800–950 and 1100–1350 km depths beneath a number of the hotspots. Their presence implies that the chemistry and thermodynamics of the mid-mantle may be more complex than suggested by seismic tomography.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".