Multiplicity of cool dwarfs
Bibliographic record
Abstract
Abstract Multiple systems have long been used to probe the origin and evolution of stars of all masses. Only in the past 10–15 years have such studies been extended to brown dwarfs and the lowest mass stars through binary surveys of both young star forming regions and the older field population. In addition, a groundswell of interest in M dwarfs in recent years has resulted in large, modern datasets for these most common stars in the Galaxy, thereby enabling renewed perspectives on their multiplicity properties. These latest observational results have in turn fueled the many theories competing to explain the formation of low‐mass stars and brown dwarfs. This Cool Stars 17 splinter session examined the current state of this field by reviewing results from the numerous observational techniques – radial velocities, astrometry, direct imaging, and synoptic surveys – that have been used to study multiplicity from the earliest embedded protostars to objects in young star forming regions, old and intermediate‐age clusters, as well as the more heterogeneous field population. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".