Student Competition (Technology Innovation) ID 1985155
Bibliographic record
Abstract
Background ISMS entails implanting micro-electrodes into the spinal cord to produce synergistic activations of the legs. To date, ISMS has produced in-place stepping in cats with complete spinal cord injury (SCI) (Saigal et al, 2004), and long distances of over ground walking in anesthetized cats (Holinski et al, 2016). Objective The goal of this project is to develop an intervention for restoring overground walking capacity for persons experiencing paralysis due to SCI, by investigating the potential of ISMS to enable long-distance overground walking in cats with chronic SCI. Method Experiments will be performed in eight adult cats with chronic complete SCI. The control strategy will include timed transitions between different phases of the step cycle, which will be modified using feedback from force plates and gyroscopes. The biomechanics of walking (speed of walking, stride length, left-right symmetry, inter-joint coordination) and muscle activation patterns will be recorded and analyzed. The stride-to-stride regularity of walking, amount of weight-bearing, and level of spasticity before, during, and after ISMS will be assessed. Results We expect that ISMS will produce long distances of walking (>500 m) in cats with SCI. The biomechanical features of walking will be similar to those in neurologically-intact cats. Conclusion This project is a critical step towards demonstrating the viability of ISMS as a means for restoring functional walking after severe SCI. If successful, ISMS and the control strategies developed may in the future change the lives of many people living with SCI, giving them the capability to walk independently.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.912 | 0.832 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".