The Use of Intraoperative Neurophysiological Monitoring in Spine Surgery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
STUDY DESIGN: Narrative review. OBJECTIVE: To summarize relevant studies regarding the utilization of intraoperative neurophysiological monitoring (IONM) techniques in spine surgery implemented in recent years. METHODS: A literature search of the Medline database was performed. Relevant studies from all evidence levels have been included. Titles, abstracts, and reference lists of key articles were included. RESULTS: Multimodal intraoperative neurophysiological monitoring (MIONM) has the advantage of compensating for the limitations of each individual technique and seems to be effective and accurate for detecting perioperative neurological injury during spine surgery. CONCLUSION: Although there are no prospective studies validating the efficacy of IONM, there is a growing body of evidence supporting its use during spinal surgery. However, the lack of validated protocols to manage intraoperative alerts highlights a critical knowledge gap. Future investigation should focus on developing treatment methodology, validating practice protocols, and synthesizing clinical guidelines.
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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 | 0.001 |
| 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 it