Bibliographic record
Abstract
Context. An inner companion has recently been discovered orbiting the prototype of classical Cepheids, δ Cep, whose orbital parameters are still not fully constrained. Aims. We collected new precise radial velocity measurements of δ Cep in 2019 using the HARPS-N spectrograph mounted at the Telescopio Nazionale Galileo. Using these radial velocity measurements, we aimed to improve the orbital parameters of the system. Methods. We considered a template available in the literature as a reference for the radial velocity curve of the pulsation of the star. We then calculated the residuals between our global dataset (composed of the new 2019 observations plus data from the literature) and the template as a function of the pulsation phase and the barycentric Julian date. This provides the orbital velocity of the Cepheid component. Using a Bayesian tool, we derived the orbital parameters of the system. Results. Considering priors based on already published Gaia constraints, we find for the orbital period a maximum a posteriori probability of $ P_{\mathrm{orb}}=9.32_{-0.04}^{+0.03} $ years (uncertainties correspond to the 95% highest density probability interval), and we obtain an eccentricity $ e=0.71_{-0.02}^{+0.02} $, a semimajor axis $ a=0.029_{-0.003}^{+0.002} $ arcsec, and a center-of-mass velocity $ V_{0}=-17.28_{-0.08}^{+0.08} $ km s−1, among other parameters. Conclusions. In this short analysis we derive the orbital parameters of the δ Cep inner binary system and provide a cleaned radial velocity curve of the pulsation of the star, which will be used to study its Baade–Wesselink projection factor in a future publication.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".