Bibliographic record
Abstract
The desire to bring space travel to a wider range of missions and uses has driven the market to using smaller and thus more affordable satellite systems. The Canadian Space Agency is completing the design and construction of a small satellite named QuickSat, which will utilize a magnetometer as one of its attitude and orbit determination instruments. A test bed comprised of three pairs of Helmholtz coils was used for hardware in the loop testing of the magnetometer. Testing was initially completed to prove the capabilities of the test bed, and then was completed to demonstrate the capabilities of the flight qualified magnetometer. The three pairs of Helmholtz coils were driven by data calculated from a spherical harmonic model of the Earth's magnetic field The coils were controlled using a robust controller and the magnetometer was used to drive the B-dot control law in the QuickSat simulation. The Ryerson Attitude and Control Experiment (RACE), which is a small satellite sized platform, free to spin about one axis on a near frictionless air bearing, was utilized to develop and test a system to deal with redundancy of satellite sensors. The possibility of missing, noisy or erroneous output during flight requires that a filter be applied to a satellite's flight code to determine with accuracy the attitude and orbit of the spacecraft. It was thus decided that a Kalman Filter be applied to RACE. The Kalman filter was applied to the RACE simulation successfully and initial hardware testing was carried out.
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.
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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".