Evolutionary Models for Ultracool Dwarfs
Bibliographic record
Abstract
Ultracool dwarfs (UCDs) have emerged as key targets for searches of transiting exoplanets. Precise estimates of the host parameters (including mass, age, and radius) are fundamental to constraining the physical properties of orbiting exoplanets. We have extended our evolutionary code Code Liégeois d'Evolution Stellaire to the UCD regime. We include relevant equations of state (EOSs) for H, He, as well as C and O elements to cover the temperature–density regime of UCD interiors. For various metallicities, we couple the interior models to two sets of model atmospheres as surface boundary conditions. We show that including C and O in the EOS has a significant effect close to the H-burning limit mass. The typical systematic error associated with uncertainties in input physics in evolutionary models is ∼0.0005 M ⊙ . We test model results against observations for objects whose parameters have been determined from independent techniques. We are able to reproduce dynamical mass measurements of LSPM J1314+1320AB within 1 σ with the condition of varying the metallicity (determined from calibrations) up to 2.5 σ . For GJ 65AB, a 2 σ agreement is obtained between individual masses from differential astrometry and those from evolutionary models. We provide tables of UCD models for various masses and metallicities that can be used as reference when estimating parameters for ultracool objects.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".