PERFORMANCE OF AN ACTIVITY MONITOR INTEGRATED INTO A MICROPROCESSOR KNEE
Bibliographic record
Abstract
INTRODUCTION
 For many years, the biomechanical evaluation of prosthetic performance has centred around gait analysis and motion capture. While this provides useful, scientific insights, everyday life is not limited to straight-line, level, steady-state walking. With advancements in portable sensor technology in the last two decades, long-term activity monitoring (AM) has become a more feasible and reliable prospect for accurately representing the real-world walking behaviour of patients. Modern microprocessor knees (MPKs) have begun to have this functionality built into the devices themselves, without the necessity for additional, external hardware.
 Abstract PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/32031/24448
 How to cite: Sykes A, Stech N, Laszczak P, McGrath M, Kercher A, Zahedi S, Moser D. PERFORMANCE OF AN ACTIVITY MONITOR INTEGRATED INTO A MICROPROCESSOR KNEE. 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.v1i2.32031 
 Abstracts were Peer-reviewed by the American Orthotic Prosthetic Association (AOPA) 101st National Assembly Scientific Committee. 
 http://www.aopanet.org/
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 | 0.000 | 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 | 0.000 |
| 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".