On the possibility of anisotropic heat flow in the inner core
Bibliographic record
Abstract
We consider the possibility of anisotropic heat flow in the inner core by examining the potential for anisotropic thermal conductivity of hexagonal close-packed (hcp-)Fe. Because hcp-Fe exists only at pressures above 13 GPa at room temperature, we investigate thermal conductivity anisotropy in analog material Gd by measuring the electrical conductivity and applying the WiedemannFranz Law to determine thermal conductivity (k). The electrical conductivity anisotropy of Gd was measured at pressures up to 1.4 GPa and temperatures up to 873 K in the hcp phase range. At elevated pressure, the variation with temperature of anisotropic thermal conductivity of Gd single crystal resembles the anisotropic behavior at high temperature and 1 atm observed in earlier work. The temperature range of anisotropy of thermal conductivity of Gd, where kc > ka, is extended by pressure, but the anisotropy disappears before the high temperature hcp[Formula: see text]bcc (body-centered cubic) transformation. Our results on hcp-Gd lead us to raise the question of the possibility of hcp-Fe exhibiting anisotropy of thermal conductivity. Together with the known seismic anisotropy of the inner core, and the inferred textural alignment of hcp crystals causing it, we suggest some implications that an anisotropy of thermal conductivity of hcp-Fe, and a concomitant anisotropy of inner core heat flow, could have on thermally driven core processes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".