The ASAS-SN catalogue of variable stars – VIII. ‘Dipper’ stars in the Lupus star-forming region
Bibliographic record
Abstract
ABSTRACT Some young stellar objects such as T Tauri-like ‘dipper’ stars vary due to transient partial occultation by circumstellar dust, and observations of this phenomenon inform us of conditions in the planet-forming zones close to these stars. Although many dipper stars have been identified with space missions such as Kepler/K2, ground-based telescopes offer longer term and multiwavelength perspectives. We identified 11 dipper stars in the Lupus star-forming region in data from the All-Sky Automated Survey for SuperNovae (ASAS-SN), and further characterized these using observations by the Las Cumbres Global Observatory Telescope (LCOGT) and the Transiting Exoplanet Survey Satellite (TESS), as well as archival data from other missions. Dipper stars were identified from a catalogue of nearby young stars and selected based on the statistical significance, asymmetry, and quasi-periodicity or aperiodicity of variability in their ASAS-SN light curves. All 11 stars lie above or redwards of the zero-age main sequence and have infrared (IR) excesses indicating the presence of full circumstellar discs. We obtain reddening–extinction relations for the variability of seven stars using our combined ASAS-SN-TESS and LCOGT photometry. In all cases, the slopes are below the ISM value, suggesting larger grains, and we find a tentative relation between the slope (grain size) and the $K_\text{s}-[22 \, \mu \text{m}]$ IR colour regarded as a proxy for disc evolutionary state.
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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 | 0.007 | 0.004 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".