STARSAT: a joint NASA/AF project for laser calibration of small objects in space
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 Air Force Research Laboratory/Directed Energy Directorate (AFRL/DE) and NASA/Marshall Space Flight Center (MSFC) are looking at a series of joint laser space calibration experiments using the 12J 15Hz CO<SUB>2</SUB> HIgh Performance CO<SUB>2</SUB> Ladar Surveillance Sensor (HI-CLASS) system on the 3.67 meter aperture Advanced Electro-Optics System (AEOS). The objectives of these experiments are to provide accurate range and signature measurements of calibration spheres, demonstrate high resolution tracking capability of small objects, and precision dray determination for LEO. Ancillary benefits include calibrating radar and optical sites, completing satellite conjunction analyses, supporting orbital perturbations analyses, and comparing radar and optical signatures. In the first experiment, a Global Positioning System (GPS)/laser beacon instrumented micro-satellite about 25 cm in diameter will be deployed from a Space Shuttle Hitchhiker canister or other suitable launch means. Orbiting in low earth orbit, the micro-satellite will pass over AEOS on the average of two times per 24-hour period. An onboard orbit propagator will activate the GPS unit and a visible laser beacon at the appropriate times. The HI-CLASS/AEOS system will detect the micro-satellite as it rises above the horizon, using GPS-generated acquisition vectors. The visible laser beacon will be used to fine-tune the tracking parameters for continuous ladar data measurements throughout the pass. This operational approach should maximize visibility to the ground-based laser while allowing battery life to be conserved, thus extending the lifetime of the satellite. GPS data will be transmitted to the ground providing independent location information for the micro-satellite down to sub-meter accuracies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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