Quantifying Variability of Young Stellar Objects in the Mid-infrared Over 6 Years with the Near-Earth Object Wide-field Infrared Survey Explorer
Bibliographic record
Abstract
Abstract Variability in young stellar objects (YSOs) can be caused by various time-dependent phenomena associated with star formation, including accretion rates, geometric changes in the circumstellar disks, stochastic hydromagnetic interactions between stellar surfaces and inner-disk edges, reconnections within the stellar magnetosphere, and hot/cold spots on stellar surfaces. We uncover and characterize ∼1700 variables from a sample of ∼5400 YSOs in nearby low-mass star-forming regions using mid-IR light curves obtained from the 6.5 yr Near-Earth Object Wide-field Infrared Survey Explorer All Sky Survey. The mid-IR variability traces a wide range of dynamical, physical, and geometrical phenomenon. We classify six types of YSO mid-IR variability based on their light curves: secular variability (linear, curved, and periodic) and stochastic variability (burst, drop, and irregular). YSOs in earlier evolutionary stages have higher fractions of variables and higher amplitudes for the variability, with the recurrence timescale of FUor-type outbursts (defined here as ΔW1 or ΔW2 > 1 mag followed by inspection of candidates) of ∼1000 yr in the early embedded protostellar phase. Known eruptive young stars and subluminous objects show fractions of variables similar to the fraction (∼55%) found in typical protostars, suggesting that these two distinct types are not distinct in variability over the 6.5 yr timescale. Along with brightness variability, we also find a diverse range of secular color variations, which can be attributed to a competitive interplay between the variable accretion luminosity of the central source and the variable extinction by material associated with the accretion process.
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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 | 0.001 |
| 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".