THE EFFECT OF MATERIAL CHOICE AND PROCESS PARAMETERS ON THE MECHANICAL STRENGTH OF 3D-PRINTED TRANSTIBIAL PROSTHETIC
Bibliographic record
Abstract
INTRODUCTION
 The most important aspect of a lower extremity prosthesis is the socket. The socket is the interface between the human and the mechanical support system1. There are different methods for producing prosthetic sockets. The traditional method requires a skilled prosthetist and is time consuming 2, 3. Using 3D printing technology for manufacturing prosthetic sockets promises to speed up the fabrication process and reduce materials and time cost significantly. 3D Printed prosthetic sockets have to potential to increase socket strength and durability. This paper investigates the effect of material choices and printing process parameters on the mechanical strength of 3D printed trans-tibial sockets.
 Abstract PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/32160/24510
 How to cite: Sabeti S, Raschke S.U, Mattie J. THE EFFECT OF MATERIAL CHOICE AND PROCESS PARAMETERS ON THE MECHANICAL STRENGTH OF 3D-PRINTED TRANSTIBIAL PROSTHETIC. CANADIAN PROSTHETICS & ORTHOTICS JOURNAL, VOLUME 1, ISSUE 2, 2018; ABSTRACT, POSTER PRESENTATION AT THE AOPA’S 101ST NATIONAL ASSEMBLY, SEPT. 26-29, VANCOUVER, CANADA, 2018. DOI: https://doi.org/10.33137/cpoj.v1i2.32160 
 Abstracts were Peer-reviewed by the American Orthotic Prosthetic Association (AOPA) 101st National Assembly Scientific Committee. 
 http://www.aopanet.org/
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".