Bibliographic record
Abstract
Radial velocity surveys find Jupiter-mass planets with semimajor axes a less than 0.1 AU around ~1% of solar-type stars; counting planets with a as large as 5 AU, the fraction of stars having planets reaches ~10% (as found by Marcy et al. and Butler et al.). An examination of the distribution of semimajor axes shows that there is a clear excess of planets with orbital periods around 3 or 4 days, corresponding to a ≈ 0.03 AU, with a sharp cutoff at shorter periods (see Fig. 1). It is believed that Jupiter-mass planets form at large distances from their parent stars; some fraction then migrates in to produce the short-period objects. We argue that a significant fraction of the hot Jupiters ( a < 0.1 AU) may arise in binary star systems in which the orbit of the binary is highly inclined to the orbit of the planet. Mutual torques between the two orbits drive down the minimum separation or periapsis r p between the planet and its host star (the Kozai mechanism). This periapsis collapse is halted when tidal friction on the planet circularizes the orbit faster than Kozai torque can excite it. The same friction then circularizes the planet orbit, producing hot Jupiters with the peak of the semimajor axis distribution lying around 3 days. For the observed distributions of binary separation, eccentricity, and mass ratio, roughly 2.5% of planets with initial semimajor axis a p ≈ 5 AU will migrate to within 0.1 AU of their parent star. Kozai migration could account for 10% or more of the observed hot Jupiters.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".