Eastern Edge Robotics: Technical Report
Bibliographic record
Abstract
This 25-page report, provided by Memorial University of Newfoundland, describes the design and construction of the underwater remotely operated vehicle (ROV) created by the Eastern Edge team for the Explorer Class of the 2024 MATE ROV competition. MATE ROV is a global competition that challenges STEM students to build underwater ROVs to complete challenges. The competition is split into the following classes based on build complexity: Explorer, Ranger, Pioneer, and Navigator, and Scout.The report begins with an abstract introducing Eastern Edge and their ROV followed by a discussion of teamwork and project management. Next, the Design Rationale section goes into detail on the design and construction of the ROV, highlighting vehicle structure, the electrical control system, software used, propulsion, buoyancy and ballast, and ROV tools. Also discussed are testing and troubleshooting strategies, ROV and team safety, and accounting. The following appendices are included:Safety Checklist for OperationsSafety Checklist for ConstructionProject ScheduleBudget TableSystem Integration DocumentManuals for each competition class and technical reports from other teams are available to view separately.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.120 | 0.158 |
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".