Exploring the Neptunian desert: insights from a homogeneous planetary sample
Bibliographic record
Abstract
ABSTRACT In this paper, we present a homogeneous analysis of close-in Neptune planets. To do this, we compile a sample of TESS-observed planets using a ranking criterion which takes into account the planet’s period, radius, and the visual magnitude of its host star. We use archival and new HARPS data to ensure every target in this sample has precise radial velocities. This yields a total of 64 targets, 46 of which are confirmed planets and 18 of which show no significant radial velocity signal. We explore the mass–radius distribution, planetary density, stellar host metallicity, and stellar and planetary companions of our targets. We find 26 per cent of our sample are in multiplanet systems, which are typically seen for planets located near the lower edge of the Neptunian desert. We define a ‘gold’ subset of our sample consisting of 33 confirmed planets with planetary radii between 2$R_{\oplus}$ and 10$R_{\oplus}$. With these targets, we calculate envelope mass fractions (EMF) using the GAS gianT modeL for Interiors (GASTLI). We find a clear split in EMF between planets with equilibrium temperatures below and above 1300 K, equivalent to an orbital period of $\sim$3.5 d. Below this period, EMFs are consistent with zero, while above they typically range from 20 per cent to 40 per cent, scaling linearly with the planetary mass. The orbital period separating these two populations coincides with the transition between the Neptunian desert and the recently identified Neptunian ridge, further suggesting that different formation and/or evolution mechanisms are at play for Neptune planets across different close-in orbital regions.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".