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Record W4390460027 · doi:10.33137/cpoj.v6i2.42139

3D PRINTING AND THE EVOLUTION OF PARTIAL HAND PROSTHESES: MY JOURNEY FROM THEORY TO PRACTICE

2023· article· en· W4390460027 on OpenAlexvenueaboutno aff
Christopher M. Baschuk

Bibliographic record

VenueCanadian Prosthetics & Orthotics Journal · 2023
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsnot available
Fundersnot available
Keywords3D printingTransformative learningProcess (computing)Computer sciencePoint (geometry)Operations managementEngineeringPsychologyMechanical engineering

Abstract

fetched live from OpenAlex

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.020
Scholarly communication0.0080.013
Open science0.0020.005
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0050.002

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.

Opus teacher head0.007
GPT teacher head0.225
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2023
Admission routes2
Has abstractyes

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