International Standards for Neurological Classification of Spinal Cord Injury: Classification Questions and Cases
Bibliographic record
Abstract
Background: The International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) have been refined through the years and continue to evolve with advances in the field. The International Standards Committee of the American Spinal Injury Association (ASIA) is responsible for maintaining, continually reviewing, and updating the ISNCSCI. Questions from spinal cord injury (SCI) professionals are frequently submitted to ASIA for review by the International Standards Committee. Methods: Of the questions submitted to the International Standards Committee, 5 were selected for this article, as they relate to common areas of confusion, address challenging classification concepts, and have not previously been described. Representative cases were also created to reinforce classification rules and the committee's recommendations. Cases: The 5 questions/cases address ISNCSCI classification in the setting of (1) AIS E grade, (2) tendon transfer, (3) spinal cord stimulation, (4) nontraumatic SCI (ntSCI) etiology, and (5) AIS D grade (vs. AIS B) based on the presence of non-key muscle function. Each case includes a detailed review of the correct classification components and thorough discussion of the impact the corresponding question has on the classification. Conclusion: The International Standards Committee provides answers to questions about ISNCSCI classification. The scenarios presented in this article address important classification rules and challenging concepts that have not previously been described. This article can serve as a useful reference when similar cases are encountered in clinical and research settings.
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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 | 0.021 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".