Characterization of M, L, and T Dwarfs in the Sloan Digital Sky Survey
Bibliographic record
Abstract
An extensive sample of M, L, and T dwarfs identified in the Sloan Digital Sky Survey (SDSS) has been compiled. The sample of 718 dwarfs includes 677 new objects (629 M dwarfs and 48 L dwarfs), together with 41 that have been previously published. All new objects and some of the previously published ones have new optical spectra obtained either with the SDSS spectrographs or with the Apache Point Observatory 3.5 m ARC telescope. Spectral types and SDSS colors are available for all objects; approximately 35% also have near-infrared magnitudes measured by 2MASS (Two Micron All Sky Survey) or on the Mauna Kea system. We use this sample to characterize the color–spectral type and color-color relations of late-type dwarfs in the SDSS filters and to derive spectroscopic and photometric parallax relations for use in future studies of the luminosity and mass functions based on SDSS data. We find that the i * - z * and i * - J colors provide good spectral type and absolute magnitude ( M i * ) estimates for M and L dwarfs. Our distance estimates for the current sample indicate that SDSS is finding early M dwarfs out to ∼1.5 kpc, L dwarfs to ∼100 pc, and T dwarfs to ∼20 pc. The T dwarf photometric data show large scatter and are therefore less reliable for spectral type and distance estimation.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 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 | 0.000 |
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".