TRANSIT TIMING VARIATION OF NEAR-RESONANCE PLANETARY PAIRS: CONFIRMATION OF 12 MULTIPLE-PLANET SYSTEMS
Bibliographic record
Abstract
We extract transit timing variation (TTV) signals for 12 pairs of transiting planet candidates that are near first-order mean motion resonances (MMR), using publicly available Kepler light curves (Q0–Q14). These pairs show significant sinusoidal TTVs with theoretically predicted periods, which demonstrate these planet candidates are orbiting and interacting in the same system. Although individual masses cannot be accurately extracted based only on TTVs because of the well-known degeneracy between mass and eccentricity, TTV phases and amplitudes can still place upper limits on the masses of the candidates, confirming their planetary nature. Furthermore, the mass ratios of these planet pairs can be relatively tightly constrained using these TTVs. The planetary pair in KOI 880 seems to have particularly high mass and density ratios, which might indicate very different internal compositions of these two planets. Some of these newly confirmed planets are also near MMR with other candidates in the system, forming unique resonance chains (e.g., KOI 500).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".