ACCESSIBLE PROSTHETIC ARMS: VICTORIA HAND PROJECT AND THE IMPACT OF 3D PRINTING
Bibliographic record
Abstract
Victoria Hand Project (VHP) is a Canadian charity with a mission to provide 3D printed prosthetic arms to people in-need across the world, by partnering with prosthetic care providers. This article explores the journey of VHP, sharing insights, lessons learned, ongoing directions, and the impact of 3D printing on prosthetic care for people with upper-limb amputation. Benefits such as affordability and customization are explored, as well as the challenges encountered, including quality control and the steep learning curve associated with working in the digital 3D space. Through this article, the potential of 3D printing to continue to transform the field of assistive technology and prosthetic and orthotic applications is underscored, especially when used for collaborative, humanitarian initiatives. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/42142/32202 How To Cite: Dechev N, Knights K, Arklie K, Martindale M, Peirone M. Accessible prosthetic arms: Victoria Hand Project and the impact of 3D printing. Canadian Prosthetics & Orthotics Journal. 2023; Volume 6, Issue 2, No.9. https://doi.org/10.33137/cpoj.v6i2.42142 Corresponding Author: Nick Dechev, PhDBiomedical Designs and Systems Laboratory, University of Victoria, Victoria, V8P 5C2 Canada.E-Mail: dechev@uvic.caORCID ID: https://orcid.org/0000-0002-7731-0280
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".