Bibliographic record
Abstract
Abstract Understanding the anomalous radii of many transiting hot gas-giant planets is a fundamental problem of planetary science. Recent detections of reinflated warm Jupiters orbiting post-main-sequence stars and the reinflation of hot Jupiters while their host stars evolve on the main sequence may help constrain models for the anomalous radii of hot Jupiters. In this work, we present evolution models studying the reinflation of gas giants to determine how varying the depth and intensity of deposited heating affects both main-sequence reinflation of hot Jupiters and post-main-sequence reinflation of warm Jupiters. We find that deeper heating is required to reinflate hot Jupiters than is needed to suppress their cooling, and that the timescale of reinflation decreases with increasing heating rate and depth. We find a strong degeneracy between heating rate and depth, with either strong shallow heating or weak deep heating providing an explanation for main-sequence reinflation of hot Jupiters. This degeneracy between heating rate and depth can be broken in the case of post-main-sequence reinflation of warm Jupiters, as the inflation must be rapid to occur within post-main-sequence evolution timescales. We also show that the dependence of heating rate on the incident stellar flux inferred from the sample of hot Jupiters can explain reinflation of both warm and hot Jupiters. TESS will obtain a large sample of warm Jupiters orbiting post-main-sequence stars, which will help to constrain the mechanism(s) causing the anomalous radii of gas-giant planets.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".