The impact of Rayleigh number on assessing the significance of supercontinent insulation
Bibliographic record
Abstract
Several processes unfold during the supercontinent cycle, more than one of which might result in an elevation in subcontinental mantle temperatures, thus multiple interpretations of the concept of continental insulation exist. Although a consensus seems to have formed that subcontinental mantle upwellings appear below large continents extensively ringed by subduction zones, there are differing views on what role continental insulation plays in the production of elevated mantle temperatures. Here we investigate how the heating mode of the mantle can change the influence of the “thermal blanket” effect. We present 2‒D and 3‒D Cartesian geometry mantle convection simulations with thermally and mechanically distinct oceanic and continental plates. The evolution of mantle thermal structure is examined after continental accretion at subduction zones (e.g., the formation of Pangea) for a variety of different mantle‒heating modes. Our results show that in low‒Rayleigh number models the impact of the role of continental insulation on subcontinental temperatures increases, when compared to models with higher convective vigor. Broad, hot upper mantle features generated in low‒Rayleigh number models (due, in part, to the thermal blanket effect) are absent at higher Rayleigh numbers. We find that subcontinental heating in a high‒Rayleigh number flow occurs almost entirely as a consequence of the influence of subduction initiation at the continental margin, rather than the influence of continental insulation. In our models featuring Earth‒like convective vigor, we find that it is difficult to obtain subcontinental temperatures in significant excess of suboceanic temperatures over timescales relevant to supercontinent aggregation.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".