Obliquities of exoplanet host stars
Bibliographic record
Abstract
Measurements of the obliquities in exoplanet systems have revealed some remarkable architectures, some of which are very different from the Solar System. Nearly 200 obliquity measurements have been obtained through observations of the Rossiter–McLaughlin (RM) effect. Here, we report on observations of 19 planetary systems that led to 17 clear detections of the RM effect and 2 less secure detections. After adding the new measurements to the tally, we used the entire collection of RM measurements to investigate four issues that have arisen in the literature. i) Does the obliquity distribution show a peak at approximately 90°? We find tentative evidence that such a peak does exist when restricting attention to the sample of sub-Saturn planets and hot Jupiters orbiting F stars. ii) Are high obliquities associated with high eccentricities? We find the association to be weaker than previously reported, and that a stronger association exists between obliquity and orbital separation, possibly due to tidal obliquity damping at small separations. iii) How low are the lowest known obliquities? Among hot Jupiters around cool stars, we find the dispersion to be 1.4 ± 0.7°, smaller than the 6° obliquity of the Sun, which serves as additional evidence for tidal damping. iv) What are the obliquities of stars with compact and flat systems of multiple planets? We find that they generally have obliquities lower than 10°, with several remarkable exceptions possibly caused by wide-orbiting stellar or planetary companions.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".