USE OF EXTERNALLY-POWERED ORTHOSIS TO ADDRESS COMPLEXITIES ASSOCIATED WITH BILATERAL BRACHIAL PLEXOPATHY
Bibliographic record
Abstract
INTRODUCTION Brachial plexus injuries are often caused by trauma, tumors or inflammation. The severity of the injury may vary, however in most traumatic cases, the supraclavicular region is impacted. Depending on the severity of the injury, surgery is often indicated early due to the likelihood of nerve regeneration. Surgical procedures include neurolysis, nerve grafting and neurotisation; where approximately 45% will regain adequate function to perform activities of daily living (ADLs) and return to work. According to current data, approximately 9,700 individuals per year will remain disabled due to the injury. For individuals where surgical intervention has not provided improvement in function, alternative solutions must be investigated. Particularly for those with bilateral involvement, potential solutions include orthotic technology. Like users of prosthetic technology, there is a wide array of technology available, intended to meet the diverse needs experienced by the population of individual who have lost function of the upper limbs. This paper describes the challenges experienced by an individual with bilateral brachial plexus injuries and addresses the case solutions using collaborative inter-professional practice.1-4 Abstract PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/32047/24461 How to cite: Delgado C, Latour D. USE OF EXTERNALLY-POWERED ORTHOSIS TO ADDRESS COMPLEXITIES ASSOCIATED WITH BILATERAL BRACHIAL PLEXOPATHY. CANADIAN PROSTHETICS & ORTHOTICS JOURNAL, VOLUME 1, ISSUE 2, 2018; ABSTRACT, ORAL PRESENTATION AT THE AOPA’S 101ST NATIONAL ASSEMBLY, SEPT. 26-29, VANCOUVER, CANADA, 2018. DOI: https://doi.org/10.33137/cpoj.v1i2.32047 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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".