Using HARPS-N to characterise the long-period planets in the PH-2 and Kepler-103 systems
Bibliographic record
Abstract
We present confirmation of the planetary nature of PH-2b, as well as the first mass estimates for the two planets in the Kepler-103 system. PH-2b and Kepler-103c are both long-period and transiting, a sparsely-populated category of exoplanet. We use {\it Kepler} light-curve data to estimate a radius, and then use HARPS-N radial velocities to determine the semi-amplitude of the stellar reflex motion and, hence, the planet mass. For PH-2b we recover a 3.5-$\sigma$ mass estimate of $M_p = 109^{+30}_{-32}$ M$_\oplus$ and a radius of $R_p = 9.49\pm0.16$ R$_\oplus$. This means that PH-2b has a Saturn-like bulk density and is the only planet of this type with an orbital period $P > 200$ days that orbits a single star. We find that Kepler-103b has a mass of $M_{\text{p,b}} = 11.7^{+4.31}_{-4.72}$ M$_{\oplus}$ and Kepler-103c has a mass of $M_{\text{p,c}} = 58.5^{+11.2}_{-11.4}$ M$_{\oplus}$. These are 2.5$\sigma$ and 5$\sigma$ results, respectively. With radii of $R_{\text{p,b}} = 3.49^{+0.06}_{-0.05}$ R$_\oplus$, and $R_{\text{p,c}} = 5.45^{+0.18}_{-0.17}$ R$_\oplus$, these results suggest that Kepler-103b has a Neptune-like density, while Kepler-103c is one of the highest density planets with a period $P > 100$ days. By providing high-precision estimates for the masses of the long-period, intermediate-mass planets PH-2b and Kepler-103c, we increase the sample of long-period planets with known masses and radii, which will improve our understanding of the mass-radius relation across the full range of exoplanet masses and radii.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".