Deviation of Mercury's spin axis from an exact Cassini state induced by dissipation
Bibliographic record
Abstract
We compute predictions of the deviation of Mercury’s spin axis from an exact Cassini state caused by tidal dissipation, and viscous and electromagnetic (EM) friction at the core-mantle boundary (CMB) and inner core boundary (ICB). Viscous friction at the CMB results in a phase lead; viscous and EM friction at the ICB produce a phase lag. The magnitude of the deviation from viscous and EM coupling depends on the inner core size, the kinematic viscosity and magnetic field strength, but cannot exceed an upper bound. For a small inner core, viscous friction at the CMB produces a phase lead which does not exceed 0.027 arcsec. For a large inner core (radius > 1000 km), EM friction at the ICB results in the largest phase lag, but it does not exceed 0.1 arcsec. For both viscous and EM coupling, elastic deformations induced by the misaligned fluid core and inner core play a first order role in the resulting mantle phase. Tidal dissipation results in a phase lag and its magnitude (in units of arcsec) is given by the empirical relation (80/Q), where Q is the quality factor; Q=80 results in a phase lag of ~1 arcsec. A large inner core with a low viscosity of the order of 10 17 Pa s or lower can significantly affect Q and thus the resulting phase lag. The limited mantle phase lag suggested by observations (~10 arcsec) implies a lower limit on the bulk mantle viscosity of approximately 10 17 Pa s.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".