Discovery of a multi-planet system orbiting the aged Sun-like star HD 224018
Bibliographic record
Abstract
Context. Exoplanetary systems show a large diversity of architectures and planet types. Among the increasing number of exodemographics studies, those exploring correlations between the presence of close-in small planets and cold Jupiters are the object of particular attention. Aims. In 2016, Kepler/K2 detected a system of two sub-Neptunes transiting the star HD 224018, one of them showing a mono-transit event. In 2017, we began a spectroscopic follow-up with HARPS-N to measure the dynamical masses of the planets using radial velocities, and collected additional transit observations using CHEOPS. Methods. We measured the fundamental physical parameters of the host star, which is an ‘old Sun’ analogue. We analysed radial velocities and photometric time series, also including data by TESS, to provide precise ephemerides, radii, masses, and bulk densities of the two planets, and possibly modelling their internal structure and composition. Results. The system turned out to be more crowded than was shown by Kepler/K2. Radial velocities revealed the presence of two additional bodies: a candidate cold companion on an eccentric orbit with a minimum mass nearly half that of Jupiter (eccentricity 0.60−0.08+0.07; semi-major axis 8.6−1.6+1.5 au), and an innermost super-Earth (orbital period 10.6413±0.0028 d; mass 4.1±0.8 M⊕) for which we discovered previously undetected transit events in Kepler/K2 photometry. TESS data revealed a second transit of one of the two companions originally observed by Kepler/K2. This allowed us to constrain its orbital period to a grid of values, the most likely being ~138 days, which would imply a mass less than 9 M⊕ at a 3σ significance level. Given the level of precision of our measurements, we were able to constrain the internal structure and composition of the second-most distant planet from the host star, a warm sub-Neptune with a bulk density of 3.9±0.5 g cm−3. Conclusions. HD 224018 hosts three close-in transiting planets in the super-Earth-to-sub-Neptune regime, and a candidate cold and eccentric massive companion. Additional follow-up is needed to better characterise the physical properties of the planets and their architecture, and to study the evolutionary history of the system.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".