Bibliographic record
Abstract
We analyze the variability in accretion-related emission lines for 40 Classical T Tauri stars to probe the extent of accretion variations in young stellar objects. Our analysis is based on multi-epoch high-resolution spectra for young stars in Tau-Aur and Cha I. For all stars, we obtain typically four spectra, covering timescales from hours to months. As proxies for the accretion rate, we use the H-alpha 10% width and the CaII-8662 line flux. We find that while the two quantities are correlated, their variability amplitude is not. Converted to accretion rates, the CaII fluxes indicate typical accretion rate changes of 0.35 dex, with 32% exceeding 0.5 dex, while H-alpha 10% width suggests changes of 0.65 dex, with 66% exceeding 0.5 dex. We conclude that CaII fluxes are a more robust quantitative indicator of accretion than H-alpha 10% width, and that intrinsic accretion rate changes typically do not exceed 0.5 dex on timescales of days to months. The maximum extent of the variability is reached after a few days, suggesting that rotation is the dominant cause of variability. We see a decline of the inferred accretion rates towards later spectral types, reflecting the dM/dt vs. M relationship. There is a gap between accretors and non-accretors, pointing to a rapid shutdown of accretion. We conclude that the ~2 orders of magnitude scatter in the dM/dt vs. M relationship is dominated by object-to-object scatter instead of intrinsic source variability.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".