Downwelling dense mantle residues and hotspot magmatism
Bibliographic record
Abstract
The geodynamic origin of melting anomalies found at the surface, often referred to as hotspots, is classically attributed to mantle plume processes. The coincidence of hotspots and regions of relatively thin lithosphere, however, questions the necessity for mantle plumes in driving hotspot magmatism, especially as the ability of mantle plumes to thin strong mantle lithosphere is disputed. Here, we propose a new mechanism for the self-sustained generation of magmatism at hotspots where the lithosphere-asthenosphere boundary occurs at < ~100 km. By considering the effects of both chemical and thermal density changes during partial melting of the mantle (using appropriate latent heat and depth-dependent thermal expansivity parameters), we find that mantle residues experience an overall instantaneous increase in density when melting occurs at < ~3 GPa. This controversial finding is due to thermal contraction of material during melting, which outweighs chemical buoyancy effects when melting at shallow pressures (where thermal expansivity is high, at ~4.91 x 10-5 K-1). These dense mantle residues have a tendency to sink beneath melting regions, driving the return flow of fertile mantle into the melting region and locally increasing magmatic production. This mechanism presents an alternative to the upwelling of hot mantle plumes for the generation of excess melt at hotspots and the genesis of large igneous provinces during continental breakup. We model the development of magma-rich margins using geodynamic numerical models and find a close match between modelled volcanic crustal thicknesses and real-world observations. “Hot”-spots and large igneous provinces, therefore, may not require the elevated temperatures commonly invoked to account for excess melting.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".