Dynamical Origin for the Collinder 132–Gulliver 21 Stream: A Mixture of Three Comoving Populations with an Age Difference of 250 Myr
Bibliographic record
Abstract
Abstract We use Gaia DR3 data to study the Collinder 132–Gulliver 21 region via the machine-learning algorithm StarGO and find eight subgroups of stars (ASCC 32, Collinder 132 gp 1–6, Gulliver 21) located in close proximity. Three comoving populations were identified among these eight subgroups: (i) a coeval 25 Myr old moving group (Collinder 132), (ii) an intermediate-age (50–100 Myr) group, and (iii) the 275 Myr old dissolving cluster Gulliver 21. These three populations form parallel diagonal stripe-shape overdensities in the U–V distribution, which differ from open clusters and stellar groups in the solar neighborhood. We name this kinematic structure the Collinder 132–Gulliver 21 stream, as it extends over 270 pc in the 3D space. The oldest population, Gulliver 21, is spatially surrounded by the Collinder 132 moving group and the intermediate-age group. Stars in the Collinder 132–Gulliver 21 stream have an age difference up to 250 Myr. Metallicity information shows a variation of 0.3 dex between the youngest and oldest populations. The formation of the Collinder 132–Gulliver 21 stream involves both star formation and dynamical heating. The youngest population (Collinder 132 moving group) with homogeneous metallicity is probably formed through filamentary star formation. The intermediate-age and oldest populations were then scattered by the Galactic bar or spiral structure resonance to intercept Collinder 132's orbit. Without mutual interaction between each population, the three populations are flying by each other currently and will become three distinct groups again in ∼50 Myr.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".