Nanosatellite Tracking Ships: From Concept To Launch In 7 Months
Bibliographic record
Abstract
The Space Flight Laboratory (SFL) at the University of Toronto Institute for Aerospace Studies and COM DEV Ltd have developed a low Earth orbit nanosatellite in less than seven months to perform rapid turnaround experiments in space to detect and study Automatic Indentification System (AIS) signals transmitted by maritime vessels. The satellite, known as "Nanosatellite Tracking Ships" (NTS) leverages both SFL's CanX-2 nanosatellite technology and Generic Nanosatellite Bus (GNB) mechanical design to house a custom AIS receiver payload developed by COM DEV Ltd. NTS was developed under an extremely tight schedule, with on-orbit results required within a year from contract start. NTS have successfully met all of its mission objectives and continues to operate in orbit. This paper outlines how SFL and COM DEV were able to rapidly design, construct and deploy a custom satellite to respond to the opportunity to bring on-orbit AIS detection services to the international community. This paper also provides an overview of the on-orbit data collected thus far outlining the capability of the spacecraft.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".