The Near-Earth Orbit Surveillance Satellite
Bibliographic record
Abstract
Defence Research and Development Canada (DRDC) and the Canadian Space Agency (CSA) are jointly working to place a microsatellite, equipped with a small optical telescope, on orbit to detect and track both "deep-space" earth orbiting objects (orbital altitudes > 5000 km), and inner-earth orbit (IEO) asteroids. The satellite will be named the Near Earth Orbit Surveillance Satellite (NEOSSat), is baselined for launch in 4th Q 2008, and will be equipped with a 15cm diameter telescope capable of detecting 19.5th magnitude stars over a 100s integration. Other important design requirements of this telescope include the ability to observe to within 45 degrees of the sun (to better detect IEO asteroids) and the ability to observe to within 20 degrees of the anti-sun direction and remain power-positive. The mission is expected to cost $11M CDN (launch costs included, but operating and ground-station costs excluded). The scientific aims of the NEOSSat mission will be described and the results of the NEOSSat Phase-A will be presented. Test observations have been conducted using the MOST ("Microvariability and Oscillations of STars") microsatellite, the inspiration for NEOSSat, and the results of these observations will be shown here; these tests validate both the general concept of using a microsatellite for these types of observations, as well as the expected performance.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
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".