Performance of the <i>Stellar Abundances and atmospheric Parameters Pipeline</i> adapted for M dwarfs
Bibliographic record
Abstract
Context. M dwarfs are important targets in the search for Earth-like exoplanets due to their small masses and low luminosities. Several ongoing and upcoming space missions are targeting M dwarfs for this reason, and the ESA PLATO mission is one of these. Aims. In order to fully characterise a planetary system the properties of the host star must be known. For M dwarfs we can derive effective temperature, surface gravity, metallicity, and abundances of various elements from spectroscopic observations in combination with photometric data. Methods. The Stellar Abundances and atmospheric Parameters Pipeline (SAPP) has been developed to serve as a prototype for one of the stellar science software within the PLATO consortium. The pipeline combines results from a spectroscopy, a photometry, an interferometry, and an asteroseismology module to derive stellar parameters for FGK-type stars. We have modified the pipeline to be able to analyse the M dwarf part of the PLATO target sample. The current version of the pipeline for M dwarfs mostly relies on spectroscopic observations. The module processing these data is based on the machine learning algorithm The Payne and fits a grid of model spectra to an observed spectrum to derive effective temperature and metallicity. We use spectra in the H-band, as the nearinfrared region is beneficial for M dwarfs because there are fewer molecular lines and they are brighter in this wavelength region than in the optical. A method based on synthetic spectra was developed for the continuum normalisation of the spectra, taking into account the pseudo-continuum formed by numerous lines of the water molecule. Photometry is used to constrain the surface gravity. Results. We tested the modified SAPP on spectra of M dwarfs from the APOGEE survey. Our validation sample of 26 stars includes stars with interferometric observations and binaries. We found a good agreement between our derived values and reference values from a range of previous studies. We estimate the overall uncertainties in the derived effective temperature, surface gravity, and metallicity to be 100 K, 0.1 dex, and 0.15 dex, respectively. Conclusions. We find that the modified SAPP performs well on M dwarfs and identify possible areas of future development that should lead to an improved precision of the derived stellar parameters.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.008 |
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".