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Record W2746358630 · doi:10.3847/1538-3881/aa83b0

A Statistical Survey of Peculiar L and T Dwarfs in SDSS, 2MASS, and WISE

2017· article· en· W2746358630 on OpenAlexaff

Bibliographic record

VenueThe Astronomical Journal · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsWestern University
Fundersnot available
KeywordsBrown dwarfSkyStellar classificationLow resolutionYoung stellar objectStatistical analysisHigh resolutionField (mathematics)

Abstract

fetched live from OpenAlex

Abstract We present the final results from a targeted search for brown dwarfs with unusual near-infrared colors. From a positional cross-match of the Sloan Digital Sky Survey (SDSS), 2-Micron All-Sky Survey (2MASS), and Wide-Field Infrared Survey Explorer ( WISE ) catalogs, we have identified 144 candidate peculiar L and T dwarfs. Spectroscopy confirms that 20 of the objects are peculiar or are candidate binaries. Of the 420 objects in our full sample 9 are young ( 2.1%) and another 8 (1.9%) are unusually red, with no signatures of youth. With a spectroscopic color of 2.58 ± 0.11 mag, one of the new objects, the L6 dwarf 2MASS J03530419+0418193, is among the reddest field dwarfs currently known and is one of the reddest objects with no signatures of youth known to date. We have also discovered another potentially very-low-gravity object, the L1 dwarf 2MASS J00133470+1109403, and independently identified the young L7 dwarf 2MASS J00440332+0228112, which was first reported by Schneider and collaborators. Our results confirm that signatures of low gravity are no longer discernible in low to moderate resolution spectra of objects older than ∼200 Myr. The 1.9% of unusually red L dwarfs that do not show other signatures of youth could be slightly older, up to ∼400 Myr. In this case a red color may be more diagnostic of moderate youth than individual spectral features. However, its is also possible that these objects are relatively metal-rich, and thus have enhanced atmospheric dust content.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.262
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2017
Admission routes1
Has abstractyes

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