Development of a Paddle Sensing System for Studying Paddle Dynamics for Dragon Boating
Bibliographic record
Abstract
Dragon Boat racing is a team sport that involves 20 paddlers in coordination racing against other teams over distances from 200 m to 2000 m. With some races being won by mere seconds, a small desynchronization of the team could mean the difference between winning and losing. Therefore being able to collect data on a rower’s stroke pattern is of great benefit to competitive teams. Using this data a coach can examine stroke profiles for all team members, and address problems as they arise during practice. The objective of this project was to further develop a paddle sensing unit (PSU) that can be used to monitor the paddling patterns of a rower. The improvements were to make the original PSU smaller, mountable to a paddle, and use wireless communication for data transfer. This involved the development of a circuit, designing a housing for the circuit on the paddle, and developing a phone application to collect the transmitted data. Discipline: Physical Sciences Faculty Mentor: Dr. Orla Aaquist
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".