The JCMT Transient Survey: Detection of Submillimeter Variability in a Class I Protostar EC 53 in Serpens Main
Bibliographic record
Abstract
Abstract During the protostellar phase of stellar evolution, accretion onto the star is expected to be variable, but this suspected variability has been difficult to detect because protostars are deeply embedded. In this paper, we describe a submillimeter luminosity burst of the Class I protostar EC 53 in Serpens Main, the first variable found during our dedicated JCMT/SCUBA-2 monitoring program of eight nearby star-forming regions. EC 53 remained quiescent for the first six months of our survey, from 2016 February to August. The submillimeter emission began to brighten in 2016 September, reached a peak brightness of 1.5 times the faint state, and has been decaying slowly since 2017 February. The change in submillimeter brightness is interpreted as dust heating in the envelope, generated by a luminosity increase of the protostar of a factor of ≥4. The 850 μm light curve resembles the historical K-band light curve, which varies by a factor of ∼6 with a 543 period and is interpreted as accretion variability excited by interactions between the accretion disk and a close binary system. The predictable detections of accretion variability observed at both near-infrared and submillimeter wavelengths make the system a unique test-bed, enabling us to capture the moment of the accretion burst and to study the consequences of the outburst on the protostellar disk and envelope.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".