The role of magma oceans in maintaining surface water on rocky planets orbiting M-dwarfs
Bibliographic record
Abstract
ABSTRACT Earth-like planets orbiting M-dwarf stars, M-Earths, are currently the best targets to search for signatures of life. Life as we know it requires water. The habitability of M-Earths is jeopardized by water loss to space: high flux from young M-dwarf stars can drive the loss of 3–20 Earth oceans from otherwise habitable planets. We develop a 0-D box model for Earth-mass terrestrial exoplanets, orbiting within the habitable zone, which tracks water loss to space and exchange between reservoirs during an early surface magma ocean phase and the longer deep-water cycling phase. A key feature is the duration of the surface magma ocean, assumed concurrent with the runaway greenhouse. This time-scale can discriminate between desiccated planets, planets with desiccated mantles but substantial surface water, and planets with significant water sequestered in the mantle. A longer-lived surface magma ocean helps M-Earths retain water: dissolution of water in the magma provides a barrier against significant loss to space during the earliest, most active stage of the host M-dwarf, depending on the water saturation limit of the magma. Although a short-lived basal magma ocean can be beneficial to surface habitability, a long-lived basal magma ocean may sequester significant water in the mantle at the detriment of surface habitability. We find that magma oceans and deep-water cycling can maintain or recover habitable surface conditions on Earth-like planets at the inner edge of the habitable zone around late M-dwarf stars – these planets would otherwise be desiccated if they form with less than ∼10 terrestrial oceans of water.
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 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".