BRITE-Constellation: Nanosatellites for Precision Photometry of Bright Stars
Bibliographic record
Abstract
BRITE-Constellation (where BRITE stands for BRIght Target Explorer) is an international nanosatellite mission to monitor photometrically, in two colours, the brightness and temperature variations of stars generally brighter than mag(V) ≈ 4 with precision and time coverage not possible from the ground. The current mission design consists of six nanosats (hence Constellation): two from Austria, two from Canada, and two from Poland. Each 7 kg nanosat carries an optical telescope of aperture 3 cm feeding an uncooled CCD. One instrument in each pair is equipped with a blue filter; the other with a red filter. Each BRITE instrument has a wide field of view (≈24°), so up to about 15 bright stars can be observed simultaneously, sampled in 32 × 32 pixels sub-rasters. Photometry of additional fainter targets, with reduced precision but thorough time sampling, will be possible through onboard data processing. The BRITE sample is dominated by the most intrinsically luminous stars: massive stars seen at all evolutionary stages, and evolved medium-mass stars at the very end of their nuclear burning phases. The goals of BRITE-Constellation are to (1) measure p- and g-mode pulsations to probe the interiors and ages of stars through asteroseismology; (2) look for varying spots on the stars surfaces carried across the stellar disks by rotation, which are the sources of co-rotating interaction regions in the winds of the most luminous stars, probably arising from magnetic subsurface convection; and (3) search for planetary transits.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.019 |
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".