Photometric brown-dwarf classification
Bibliographic record
Abstract
We present a homogeneous sample of 1361 L and T dwarfs brighter than J = 17.5 (of which 998 are new), from an effective area of 3070 deg2, classified by the photo-type method to an accuracy of one spectral sub-type using izYJHKW1W2 photometry from SDSS+UKIDSS+WISE. Other than a small bias in the early L types, the sample is shown to be effectively complete to the magnitude limit, for all spectral types L0 to T8. The nature of the bias is an incompleteness estimated at 3% because peculiar blue L dwarfs of type L4 and earlier are classified late M. There is a corresponding overcompleteness because peculiar red (likely young) late M dwarfs are classified early L. Contamination of the sample is confirmed to be small: so far spectroscopy has been obtained for 19 sources in the catalogue and all are confirmed to be ultracool dwarfs. We provide coordinates and izYJHKW1W2 photometry of all sources. We identify an apparent discontinuity, Δm ~ 0.4 mag, in the Y − K colour between spectral types L7 and L8. We present near-infrared spectra of nine sources identified by photo-type as peculiar, including a new low-gravity source ULAS J005505.68+013436.0, with spectroscopic classification L2γ. We provide revised izYJHKW1W2 template colours for late M dwarfs, types M7 to M9.
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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 | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
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".