SUBSTELLAR OBJECTS IN NEARBY YOUNG CLUSTERS (SONYC). V. NEW BROWN DWARFS IN ρ OPHIUCHI
Bibliographic record
Abstract
SONYC—Substellar Objects in Nearby Young Clusters—is a survey program to investigate the frequency and properties of substellar objects with masses down to a few times that of Jupiter in nearby star-forming regions. For the ∼1 Myr old ρ Ophiuchi cluster, in our earlier paper we reported deep, wide-field optical and near-infrared imaging using Subaru, combined with Two Micron All Sky Survey and Spitzer photometry, as well as follow-up spectroscopy confirming three likely cluster members, including a new brown dwarf with a mass close to the deuterium-burning limit. Here we present the results of extensive new spectroscopy targeting a total of ∼100 candidates in ρ Oph, with Fiber Multi Object Spectrograph at the Subaru Telescope and SINFONI at the ESO's Very Large Telescope. We identify 19 objects with effective temperatures at or below 3200 K, eight of which are newly identified very low mass probable members of ρ Oph. Among these eight, six objects have T eff ⩽ 3000 K, confirming their likely substellar nature. These six new brown dwarfs comprise one-fifth of the known substellar population in ρ Oph. We estimate that the number of missing substellar objects in our survey area is ∼15, down to 0.003–0.03 M ☉ and for A V = 0–15. The upper limit on the low-mass star to brown dwarf ratio in ρ Oph is 5.1 ± 1.4, while the disk fractions are ∼40% and ∼60% for stars and brown dwarfs, respectively. Both results are in line with those for other nearby star-forming regions.
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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".