BANYAN. IV. FUNDAMENTAL PARAMETERS OF LOW-MASS STAR CANDIDATES IN NEARBY YOUNG STELLAR KINEMATIC GROUPS—ISOCHRONAL AGE DETERMINATION USING MAGNETIC EVOLUTIONARY MODELS
Bibliographic record
Abstract
Based on high resolution optical spectra obtained with ESPaDOnS at CFHT, we determine fundamental parameters (\\Teff, R, \\Lbol, \\logg\\ and metallicity) for 59 candidate members of nearby young kinematic groups. The candidates were identified through the BANYAN Bayesian inference method of \\citet{2013malo}, which takes into account the position, proper motion, magnitude, color, radial velocity and parallax (when available) to establish a membership probability. The derived parameters are compared to Dartmouth Magnetic evolutionary models and to field stars with the goal to constrain the age of our candidates. We find that, in general, low-mass stars in our sample are more luminous and have inflated radii compared to older stars, a trend expected for pre-main sequence stars. The Dartmouth Magnetic evolutionary models show a good fit to observations of field K and M stars assuming a magnetic field strength of a few kG, as typically observed for cool stars. Using the low-mass members of βPictoris moving group, we have re-examined the age inconsistency problem between Lithium Depletion age and isochronal age (Hertzspring-Russell diagram). We find that the inclusion of the magnetic field in evolutionary models increase the isochronal age estimates for the K5V-M5V stars. Using these models and field strengths, we derive an average isochronal age between 15 and 28 Myr and we confirm a clear Lithium Depletion Boundary from which an age of 26±3~Myr is derived, consistent with previous age estimates based on this method.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".