Searching for T dwarfs in the ρ Oph dark cloud L 1688
Bibliographic record
Abstract
We present a list of T dwarf candidates in the dark cloud L 1688 in the ρ Oph star-forming region. These candidates are selected with infrared colours sensitive to T dwarf characteristics of methane absorptions and of cool atmospheres. The 1.6-μm methane feature is diagnosed by on–off imaging using an H-band and an intermediate-band methane filter, calibrated to a set of known brown dwarfs of M, L, and T types in the field. Another methane feature at 3.3 μm is traced with the Spitzer/Infrared Array Camera (IRAC) [3.6] − [4.5] colour. For cool atmospheres, the H − [4.5] and K − [4.5] colours are utilized. With an additional criterion of mid-infrared brightness to eliminate extragalactic interlopers, a total of 28 T dwarf candidates have been identified. A comprehensive assessment was conducted to estimate the level of contamination of our sample by young stellar variability, by extragalactic sources sharing the same colour behaviour, or by foreground T dwarfs. Though extragalactic sources may contribute up to about half of the false positives, our candidates show close spatial association with the dark cloud, rather than randomly distributed as a background population would have been. Furthermore, even though our candidates are not selected a priori by a colour–magnitude relation, they mostly follow the 1 Myr isochrones, ascertaining their youth. Our selection methodology provides guidance to search for T dwarfs in other star-forming regions. Our candidate list, when comparing with those in the literature, which often rely on a single criterion on cool temperature or methane, is more conservative but should be more secure for follow-up spectroscopic confirmation of a T dwarf sample at the early evolutionary stage.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".