Software System in Hyperloop Pod
Bibliographic record
Abstract
The Hyperloop is high-speed ground-based transportation system concept; a supersonic train line stretching across the country in airless tubes, which stands as competition for air, train, and car transportation for distances of travel from 200 to 1100 km. This paper concentrates on software - applied in the Hyperloop pod called Goose 3 [1], which was developed by the team from University of Waterloo [2] - Waterloop [3]. This paper is concentrated on roadblocks, that were faced during the design and development process; to be more specific - building a reliable and scalable infrastructure that allows for complete control of the pod throughout the launch. In the pod, electronics and software play a crucial role, as traveling at high velocities requires immediate response to real-time vehicle conditions obtained from sensors on-board, which raises it's own unique challenges. This paper looks at the work completed by team Waterloop in areas of design of the electrical and software system.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".