Student Competition (Knowledge Generation) ID 1985158
Bibliographic record
Abstract
Background Spinal cord injury (SCI) affects locomotion and quality of life. Two spinal cord stimulation approaches are currently under investigation for restoring standing and walking following SCI: epidural spinal cord stimulation (ESCS) and intraspinal microstimulation (ISMS). In ESCS, electrodes are placed on the dura mater and in ISMS, ultrafine wires are inserted into the cord. These modalities likely activate the locomotor regions in the ventral horn through different pathways. Objective The goal of this study is to examine the difference in the distribution of neuronal activation and the type of neurons activated by ESCS and ISMS. Methods The first step was to establish the needed immunohistochemical (IHC) staining protocols. Domestic pigs were divided into naïve (n=2) and positive control (n=1) groups. The naïve control animals were anesthetized for 5 hrs. The positive control animal was anesthetized for 2 hrs and injected with hypertonic saline in hindlimb muscles. The animals were then euthanized, and the spinal cord removed for IHC analysis. Antibodies against cFos, a maker of neuronal activation, and NeuN, a neuronal marker were used. Results Preliminary results indicate that ESCS activates neurons in the dorsal horn with scattered activation in the intermediate and ventral regions. ISMS primarily activates neurons in the intermediate and ventral regions where locomotor-related networks reside. Significance To the best of our knowledge, this is the first time the type and sites of activation of ESCS and ISMS are investigated. This will provide a foundational understanding of the mechanism of action of these stimulation modalities.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.926 | 0.842 |
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".