Separating Super-puffs versus Hot Jupiters among Young Puffy Planets
Bibliographic record
Abstract
Abstract Discoveries of close-in young puffy (R p ≳ 6 R ⊕) planets raise the question of whether they are bona fide hot Jupiters or puffed-up Neptunes, potentially placing constraints on the formation location and timescale of hot Jupiters. Obtaining mass measurements for these planets is challenging due to stellar activity and noisy spectra. Therefore, we aim to provide independent theoretical constraints on the masses of these young planets based on their radii, incident fluxes, and ages, benchmarking to the planets of age <1 Gyr detected by Kepler, K2, and the Transiting Exoplanet Survey Satellite. Through a combination of interior structure models, considerations of photoevaporative mass loss, and empirical mass–metallicity trends, we present the range of possible masses for 22 planets with an age of ∼10–900 Myr and radii of ∼6–16 R ⊕. We generally find that our mass estimates are in agreement with the measured masses and upper limits where applicable. There exist some outliers including super-puffs Kepler-51 b, c and V1298 Tau d, b, e, for which we outline their likely formation conditions. Our analyses demonstrate that most of the youngest planets (≲100 Myr) tend to be puffed-up, Neptune-mass planets, while the true hot Jupiters are typically found around stars aged at least a few hundred Myr, suggesting the dominant origin of hot Jupiters to be late-stage high-eccentricity migration.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".