Bibliographic record
Abstract
Our understanding of the pathophysiological processes that comprise the early secondary phases of spinal cord injury such as spinal cord ischemia, cellular excitotoxicity, ionic dysregulation, and free-radical mediated peroxidation is far greater now than ever before, thanks to substantial laboratory research efforts. These discoveries are now being translated into the clinical realm and have led to targeted upfront medical management with a focus on tissue oxygenation and perfusion and include avoidance of hypotension, induction of hypertension, early transfer to specialized centers, and close monitoring in a critical care setting. There is also active exploration of neuroprotective and neuroregenerative agents; a number of which are currently in late stage clinical trials including minocycline, riluzole, AC-105, SUN13837, and Cethrin. Furthermore, new data have emerged demonstrating that the timing of spinal cord decompression after injury impacts recovery and that early decompression leads to significant improvements in neurological recovery. With this review we aim to provide a concise, clinically relevant and up-to-date summary of the topic of acute spinal cord injury, highlighting recent advancements and areas where further study is needed.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".