Nearby Young Moving Groups: Statistical Methods and Challenges for Assigning Membership
Bibliographic record
Abstract
Abstract Young associations, being sparsely populated and relatively close to the Sun, their members are found all over the sky. In the Solar Neighborhood, young moving groups are found within 100 pc with ages ranging from 5 to 120 Myr. While known members of these groups were identified mostly through the Hipparcos data, only the most massive members have been fully characterized so far, and defined the core members. In the last decades, several new candidate members have been identified, using different approaches. Based on the global properties of the core members (kinematics and over luminosity), those methods used several criteria to establish the membership, from qualitative manner to quantitive methods using reduced chi-squared or membership probability. A full confirmation of the membership for those numerous candidates requires radial velocity and parallax measurements to confirm their kinematics, age-dating indicator measurement to assess their youth and multiplicity follow-up to rule out binary objects. In this proceeding, we summarize a general recipe to assign membership, describe the numerous challenges for assigning membership, and end with a discussion on the appropriateness and reliability of the BANYAN I and II tools to assess membership.
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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 | 0.115 | 0.287 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".