LESSONS FROM THE INAUGURAL SATELLITE DESIGN CHALLENGE
Bibliographic record
Abstract
The inaugural Canadian Satellite Design Challenge provided many experiential learning opportunities for students through the design, implementation, and testing of the T-Sat1 nanosatellite.The University of Manitoba team elected to build all components from the ground up in order to develop many technical and non-technical skills that complement the classroom experience.The first phases of the project focused on the definition of requirements, specifications, and interfaces. Then, the team began prototyping, implementing, and integrating subsystems. Finally, the spacecraft was tested at the Canadian Space Agency laboratories in Ottawa and obtained second place overall in the competition.This paper describes some of the major lessons from the implementation, integration, and testing phases of the project. In addition, some insight is provided as to the ongoing changes for the second iteration of the competition that aim at improving the experience and performance of the satellite.
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".