L<i>i</i>DO: Discovery of a 10:1 Resonator with a Novel Libration State
Bibliographic record
Abstract
Abstract The Large inclination Distant Objects (LiDO) survey has discovered the first securely classified object in the 10:1 mean motion resonance of Neptune. This object, 2020 VN40, is short-term stable in the 10:1 resonance, but not stable on Gyr timescales. 2020 VN40 is likely part of the scattering sticking population, and temporarily resides in the 10:1 resonance at ∼139.5 au. This discovery confirms that this distant resonance is populated, as a single detection is likely to be indicative of a large population that is difficult to detect due to observational biases. This object has an inclination of 33 . ° 4, and n-body integrations of orbital clones of 2020 VN40 have revealed some unexpected evolutions. While clones of 2020 VN40 show resonant libration around the expected resonance centers of approximately 90°, 180°, and 270°, for a restricted range of inclination and eccentricity values some clones librate around a resonant argument of 0°. As this occurs for the slightly lower-eccentricity portions of the evolution, this behavior can also be quite stable. Our initial exploration suggests that this libration around a center of 0° is a generic effect for highly inclined objects in n:1 resonances because the nature of their resonant interaction with Neptune becomes a strong function of their argument of pericenter, ω. At large inclination, the resonant islands shift as ω precesses, switching the center of symmetric libration to 0° for ω = 90° and ω = 270°. 2020 VN40 provides interesting insight into the evolution of the large-inclination resonators, which become more common at increasing semimajor axes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".