Bibliographic record
Abstract
A significant fraction of Kepler systems are closely packed, largely coplanar, and circular. We study the stability of a six-planet system, Kepler-11, to gain insights on the dynamics and formation history of such systems. Using a technique called "frequency maps" as fast indicators of long-term stability, we explore the stability of the Kepler-11 system by analyzing the neighborhood space around its orbital parameters. Frequency maps provide a visual representation of chaos and stability, and their dependence on orbital parameters. We find that the current system is stable, but lies within a few percent of several dynamically dangerous two-body mean-motion resonances. Planet eccentricities are restricted below a small value, ∼0.04, for long-term stability, but planet masses can be more than twice their reported values (thus allowing for the possibility of mass loss by past photoevaporation). Based on our frequency maps, we speculate on the origin of instability in closely packed systems. We then proceed to investigate how the system could have been assembled. The stability constraints on Kepler-11 (mainly eccentricity constraints) suggest that if the system were assembled in situ, a dissipation mechanism must have been at work to neutralize the eccentricity excitation. On the other hand, if migration was responsible for assembling the planets, there has to be little differential migration among the planets to avoid them either getting trapped into mean motion resonances, or crashing into each other.
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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 | 0.000 |
| 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".