Laminar optical tomography of the hemodynamic response in the lumbar spinal cord of rats
Bibliographic record
Abstract
Intrinsic optical imaging (IOI) has emerged as a very powerful tool to assess neuronal function in small animals. Although it has been used extensively in the brain, its application to the spinal cord is rare. The inability of intrinsic optical techniques to resolve different depths and embedded gray matter hampers their capacity to distinguish larger vasculature contributions of hemodynamic signals originating from motoneuron and interneuron activation. Laminar optical tomography (LOT) is a recently-developed method that fills the gap left between IOI and diffuse optical imaging. With distinct source-detector separations, light that propagates deeper into tissues can be distinguished from light originating from the surface, providing depth sensitivity. In this work, LOT is investigated for the first time to image spinal cord activation with simultaneous IOI of the cortex in rats. Such proof of concept provides a powerful imaging modality to study spinal cord activation and disruption after injury.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".