The Effect of Core Formation on Surface Composition and Planetary Habitability
Bibliographic record
Abstract
Abstract The melt productivity of a differentiated planet's mantle is primarily controlled by its iron content, which is itself approximated by the planet's core mass fraction (CMF). Here we show that estimates of an exoplanet's CMF allows robust predictions of the thickness, composition, and mineralogy of the derivative crust. These predicted crustal compositions allow constraints to be placed on volatile cycling between surface and the deep planetary interior, with implications for the evolution of habitable planetary surfaces. Planets with large, terrestrial-like CMFs (≥0.32) will exhibit thin crusts that are inefficient at transporting surface water and other volatiles into the underlying mantle. By contrast, rocky planets with smaller CMFs (≤0.24) and higher, Mars-like, mantle iron contents will develop thick crusts capable of stabilizing hydrous minerals, which can effectively sequester volatiles into planetary interiors and act to remove surface water over timescales relevant to evolution. The extent of core formation has profound consequences for the subsequent planetary surface environment and may provide additional constraints in the hunt for habitable, Earth-like exoplanets.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".