Risk Reduction Activities for the Near-Earth Object Surveillance Satellite Project
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Near-Earth Object Surveillance Satellite (NEOSSat) is a joint project between Defence Research and Development Canada (DRDC) and the Canadian Space Agency (CSA). The NEOSSat project is developing the Canadian multi-mission micro-satellite bus to satisfy two concurrent missions: detecting and tracking of near-Earth asteroids (Near Earth Space Surveillance: the NESS mission) and obtaining metric data on deep-space satellites (High Earth Orbit Surveillance System: the HEOSS mission). To ensure both science teams can employ the NEOSSat spacecraft to its full potential, a Mission Planning System (MPS) will be developed to automate the scheduling of both the HEOSS and NESS observations. As a first risk reduction activity for the NEOSSat project, a prototype of the MPS software has been developed to help in the definition of the system requirements as well as to identify and reduce the risks associated with the development of this software system. In a second risk-reduction effort, a space-based satellite tracking experiment was conducted using the MOST (Microvariability Oscillations of STars) microsatellite. Good quality metric tracking data were obtained and the satellite brightness was estimated. This paper discusses the NEOSSat project, the MPS prototype, and the MOST satellite tracking experiment and results.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it