The ultracool-field dwarf luminosity-function and space de nsity from the Canada-France Brown Dwarf Survey ?
Bibliographic record
Abstract
Context. Thanks to recent and ongoing large scale surveys, hundreds of brown dwarfs have been discovered in the last decade. The Canada-France Brown Dwarf Survey is a wide-field survey for c ool brown dwarfs conducted with the MegaCam camera on the Canada-France-Hawaii Telescope telescope. Aims. Our objectives are to find ultracool brown dwarfs and to const rain the field brown-dwarf luminosity function and the mass function from a large and homogeneous sample of L and T dwarfs. Methods. We identify candidates in CFHT/MegaCam i 0 and z 0 images and follow them up with pointed near infrared (NIR) imaging on several telescopes. Halfway through our survey we found� 50 T dwarfs and� 170 L or ultra cool M dwarfs drawn from a larger sample of 1400 candidates with typical ultracool dwarfs i 0 − z 0 colours, found in 780 square degrees. Results. We have currently completed the NIR follow-up on a large part of the survey for all candidates from mid-L dwarfs down to the latest T dwarfs known with utracool dwarfs’ colours. T his allows us to draw on a complete and well defined sample of 10 2 ultracool dwarfs to investigate the luminosity function an d space density of field dwarfs. Conclusions. We found the density of late L5 to T0 dwarfs to be 2: 0 +0: 8 −0: 7 �10
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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 | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".