The radius distribution of M dwarf-hosted planets and its evolution
Bibliographic record
Abstract
ABSTRACT M dwarf stars are the most promising hosts for detection and characterization of small and potentially habitable planets, and provide leverage relative to solar-type stars to test models of planet formation and evolution. Using Gaia astrometry, adaptive optics imaging, and calibrated gyrochronologic relations to estimate stellar properties and filter binaries, we refined the radii of 117 Kepler objects of interest (confirmed or candidate planets) transiting 74 single late K-type and early M-type stars, and assigned stellar rotation-based ages to 113 of these. We constructed the radius distribution of 115 small (${\lt} 4\, {\rm R}_{\rm{\oplus}}$) planets and assessed their evolution. As for solar-type stars, the inferred distribution contains distinct populations of ‘super-Earths’ (at ${\sim} 1.3 \, {\rm R}_{\rm{\oplus}}$) and ‘sub-Neptunes’ (at ${\sim} 2.2 \, {\rm R}_{\rm{\oplus}}$) separated by a gap or ‘valley’ at ${\approx} 1.7 \, {\rm R}_{\rm{\oplus}}$ that has a period dependence that is significantly weaker (power-law index of −0.03$^{+0.01}_{-0.03}$) than for solar-type stars. Sub-Neptunes are largely absent at short periods (${\lt} 2 \, {\rm d}$) and high irradiance, a feature analogous to the ‘Neptune desert’ observed around solar-type stars. The relative number of sub-Neptunes to super-Earths declines between the younger and older halves of the sample (median age 3.86 Gyr), although the formal significance is low ($p = 0.08$) because of the small sample size. The decline in sub-Neptunes appears to be more pronounced on wider orbits and low stellar irradiance. This is not due to detection bias and suggests a role for H2O as steam in inflating the radii of sub-Neptunes and/or regulating the escape of H/He from them.
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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 | 0.001 | 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) | 0.001 | 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".