A JWST binary survey at the cold and low-mass end of star formation
Bibliographic record
Abstract
As binarity is a direct outcome of formation, studying multiplicity across all ranges of masses and separations is key to fully understand stellar formation mechanisms. Here, we present results from a JWST/NIRCam+NIRISS campaign aimed at investigating the multiplicity of the coldest and least massive objects produced by star-forming processes. We searched for close binary companions to 22 nearby Y-type brown dwarfs, all cooler than 500 K, that represent the bottom end of the observed Initial Mass Function in the Solar neighborhood. One binary system, WISE 0336 AB, was discovered in our search and represents the first Y+Y binary system. With an estimated temperature of smaller than 300 K, the companion bridges the gap between the coldest known brown dwarf, WISE 0855, and the rest of the Y-type population. Thanks to JWST’s exceptional infrared sensitivity to extremely cold objects, and its unmatched spatial resolution at these wavelengths, we placed strong constraints on the multiplicity outputs of star formation inside unexplored regions of the parameter space, allowing to test whether the trends in companion occurrence rate, separation and mass ratio distribution seen for more massive objects extend down to the very lowest masses and temperatures.
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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 | 0.001 |
| 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 | 0.001 |
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".