3D PRINTING AND THE EVOLUTION OF PARTIAL HAND PROSTHESES: MY JOURNEY FROM THEORY TO PRACTICE
Bibliographic record
Abstract
The world of prosthetics has been undergoing significant changes, with the evolution of materials, design techniques, and manufacturing methodologies converging to redefine the landscape. Central to this narrative is the imperative for a holistic approach, harmonizing the trinity of materials, design, and methodologies to yield optimal outcomes. This balance is especially pivotal for the overlooked yet significant segment of those with partial hand and finger differences. Historically, this demographic has been underserved, with rehabilitation and prosthetic innovations often falling short. The sheer prevalence of partial hand differences underscores the urgency of tailored solutions. Traditional fabrication methods like wet lamination have posed challenges, particularly in aligning and efficiency. The advent of additive manufacturing has been transformative. The case of designing and printing a partial finger socket for Point Designs, LLC's Point Partial finger highlights this paradigm shift. Where conventional techniques demanded hours, digital design and 3D printing have condensed the process to mere minutes, without compromising on quality. This is not merely a win in terms of time efficiency; the implications for the end users are profound, ensuring a more customized and efficient solution. The journey underscores the potential of blending technology and traditional prosthetic knowledge, pointing towards a future where prosthetics align more seamlessly with users' needs. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/42139/32198 How To Cite: Baschuk C.M. 3D printing and the evolution of partial hand prostheses: my journey from theory to practice. Canadian Prosthetics & Orthotics Journal. 2023; Volume 6, Issue 2, No.5. https://doi.org/10.33137/cpoj.v6i2.42139 Corresponding Author: Christopher M Baschuk, MPO, CPO, FAAOP(D)Point Designs, LLC, Bountiful, UT, USA.E-mMail: chris@pointdesignsllc.comORCID ID: https://orcid.org/0000-0002-9895-5897
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".