Diversity of close-in planets and the interactions with their host stars
Bibliographic record
Abstract
Abstract Short period planets provide an exciting opportunity of constraining structural properties. Observations have revealed a diverse class of objects, including several at odds with aspects of conventional planet formation theories. Here we present several scenarios that may help in producing the observed diversity. For short period planets in particular, their proximity to their host stars suggests that star-planet interactions may play an important role in their orbital and structural evolution. We first show that the penetration of a non-synchronous stellar magnetic field into short period planets will provide a significant source of energy for planetary expansion and may help stall inward migration. In addition to magnetic dissipation, the intense irradiation from the host star will drive atmospheric flows, whose behaviour is strongly influenced by the opacity of the envelope. Finally, we explore the role of late stage planetesimal and embryo bombardment on the structure of gas-giant planets. Dynamical trapping during migration, followed by orbital destablization during the final stage of gas-giant growth, leads to a surge in the collision rate. Such collisions will lead to preferential core growth and inflated radii. All three of these processes, occurring late in the planetary formation process, will produce a large range in planetary properties and may account for the diversity we see today.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".