EVALUATION OF LOCALIZED PAIN IN THE TRANSTIBIAL RESIDUAL LIMB
Bibliographic record
Abstract
PURPOSE The socket is the main component of a prosthesis which surrounds the residual limb and transfers loads and motions between the residual limb and prosthesis. A misfit socket may lead to excessive stresses on the residual limb, pistoning of the prosthesis during walking, patient discomfort, pain, and skin damage. The quality of socket-skin interface directly affects quality of life, prosthesis use, and satisfaction from prosthesis in amputees. Pain is a devastating condition that prohibits prosthesis use1-4. The present study aimed to evaluate pain threshold and tolerance of the transtibial residual limb to improve its socket design and fit. Abstract PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/32028/24445 How to cite: Ghoseiri K, Rastkhadiv M.Y, Allami M. EVALUATION OF LOCALIZED PAIN IN THE TRANSTIBIAL RESIDUAL LIMB. 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.v1i2.32028 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".