Unveiling the infrared excess of SIPS J2045–6332: evidence for a young stellar object with potential low-mass companion
Bibliographic record
Abstract
ABSTRACT The Disc Detective project, a citizen science initiative, aims to identify circumstellar discs around stars by detecting objects with infrared (IR) excess using data from the Wide-field Infrared Survey Explorer (WISE). In this study, we investigate SIPS J2045–6332, a potential brown dwarf with significant IR excess in WISE and Two Micron All Sky Survey (2MASS) bands, initially identified by project volunteers. Despite early indicators of a circumstellar disc, discrepancies between observed brightness and expected spectral energy distribution (SED) models suggested unusual properties. To explore potential explanations, we created SED templates for spectral types M9 to L4 and compared them with SIPS J2045–6332’s photometric data, revealing an excess brightness that points to either an unresolved low-mass companion or a young, inflated primary star. Further analysis of IR spectral features and surface gravity indicators supports a youthful classification, estimating the object’s age at 26–200 million years. Observations also suggest the presence of a mid L-type companion at a projected distance of 6.7 au. This study highlights SIPS J2045–6332 as an intriguing system with unique IR characteristics and recommends follow-up observations with high-resolution telescopes to confirm the companion hypothesis and further characterize the system.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".