Extending the Canada-France brown dwarfs survey to the near-infrared: first ultracool brown dwarfs from CFBDSIR
Bibliographic record
Abstract
Aims. We present the first results of the ongoing Canada-France Brown Dwarfs Survey-InfraRed, hereafter CFBDSIR, a near infrared extension to the optical wide-field survey CFBDS. Our final objectives are to constrain ultracool atmosphere physics by finding a statistically significant sample of objects cooler than 650 K and to explore the ultracool brown dwarf mass function building on a well-defined sample of such objects.Methods. We identify candidates in CFHT/WIRCam J and CFHT/MegaCam z' images using optimised psf-fitting, and follow them up with pointed, near-infrared imaging with SOFI at the NTT. We finally obtain low-resolution spectroscopy of the coolest candidates to characterise their atmospheric physics.Results. We have so far analysed and followed up all candidates on the first 66 square degrees of the 335 square degree survey. We identified 55 T-dwarfs candidates with and have confirmed six of them as T-dwarfs, including 3 that are strong later-than-T8 candidates, based on their far-red and NIR colours. We also present here the NIR spectra of one of these ultracool dwarfs, CFBDSIR1458+1013, which confirms it as one of the coolest brown dwarf known, possibly in the 550–600 K temperature range. Conclusions. From the completed survey we expect to discover 10 to 15 dwarfs later than T8, more than doubling the known number of such objects. This will enable detailed studies of their extreme atmospheric properties and provide a stronger statistical basis for studies of their luminosity function.
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 | 0.002 |
| 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) | 0.002 | 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".