Attitude determination and control: Detailed design, test, and implementation for CanX-2 and preliminary design for CanX-3 and CanX-4/5
Bibliographic record
Abstract
The University of Toronto's Space Flight Laboratory develops nanosatellites through its Canadian Advanced Nanospace eXperiment (CanX) program to advance scientific understanding and engineering capabilities. Three missions are treated: CanX-2, a nanopropulsion demonstration mission that also observes greenhouse gas fluxes and upper-atmospheric water properties; CanX-3, an astronomy mission that performs differential photometry on the brightest stars in the sky; and CanX-4/5, a dual-satellite formation flight mission. The success of each mission depends, in part, on the satellites' ability to determine and control orientation, particularly in the context of payloads. This drives the need to develop a high-fidelity, robust attitude determination and control subsystem. This thesis covers the full attitude subsystem design, test, implementation, and anticipated performance of the CanX-2 mission; the preliminary attitude subsystem design for the CanX-3 and CanX-4/5 missions; and discussion of some of the infrastructure that has been developed to test the designs and support the CanX program.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".