Stellar flares detected with the Next Generation Transit Survey
Bibliographic record
Abstract
ABSTRACT We present the results of a search for stellar flares in the first data release from the Next Generation Transit Survey (NGTS). We have found 610 flares from 339 stars, with spectral types between F8 and M6, the majority of which belong to the Galactic thin disc. We have used the 13-s cadence NGTS light curves to measure flare properties such as the flare amplitude, duration, and bolometric energy. We have measured the average flare occurrence rates of K and early to mid-M stars and present a generalized method to measure these rates while accounting for changing detection sensitivities. We find that field age K and early M stars show similar flare behaviour, while fully convective M stars exhibit increased white-light flaring activity, which we attribute to their increased spin-down time. We have also studied the average flare rates of pre-main-sequence K and M stars, showing they exhibit increased flare activity relative to their main-sequence counterparts.
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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 | 0.001 |
| 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".