Dynamics of heat producing elements rich domains in rocky planets
Bibliographic record
Abstract
The isotopic compositions of lavas from mantle plumes provide evidence for deep mantle heterogeneities and have been associated with primordial mantle material. However, little is understood about how such material formed during the early stages of planetary evolution. Its origin is typically linked to processes such as the sedimentation of iron-rich phases and crystallization in a primordial magma ocean, or, alternatively, to impacts during the later stages of planetary formation. These processes operated under varying temperature and pressure conditions, likely leading to a depth-dependent composition. Regardless of how it originated, this primordial material is thought to contain higher concentrations of radioactive elements compared to the upper mantle. We aim to address a critical question: how does a compositionally stratified mantle evolve over time under convective motions. These motions reshape the boundaries of chemically distinct domains and promote mixing. Therefore, it is crucial to understand the conditions that allow primordial material to persist at the mantle's base over long timescales, particularly in relation to differences in density and heat production between various mantle components.To investigate this question, we conducted an in-depth experimental study of convection in a stratified system consisting of two fluids with distinct intrinsic densities and heat production rates. We derived scaling laws that connect the dynamical characteristics of convection to the key dimensionless numbers. These scaling laws, coupled with plausible physical parameters, are then applied to extrapolate the results to planetary mantle convection. We illustrate our approach with a diagram relating the effective partitioning coefficients of iron and that of heat producing elements to the lifetime of the stratified mantle.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".