An improved method for spinal functional MRI with large volume coverage of the spinal cord
Bibliographic record
Abstract
PURPOSE: To develop a spinal functional MRI (fMRI) method with three-dimensional coverage of a large extent of the spinal cord with minimal partial volume effects MATERIALS AND METHODS: fMRI data of the cervical spinal cord were obtained at 1.5 T with a single-shot fast spin-echo imaging method, from thin contiguous sagittal slices spanning the cord. Thermal stimulation was applied to the palm of the hand in a block pattern with 15 degrees C for stimulation and 32 degrees C during baseline periods. Prior to analysis, the image data at each time point were reformatted into three-dimensional volumes and resliced perfectly transverse to the spinal cord. Smoothing was applied only in the superior-inferior (S/I) direction across uniform tissue types. Active voxels were then identified by means of a correlation to a model paradigm. RESULTS: The resulting activity maps demonstrate activity primarily in ipsilateral sensory areas and in some motor areas, consistent with the spinal cord neuroanatomy. These data also demonstrate detail of the subsegmental organization of the spinal cord, as well as anatomical detail of the spinous processes and positions of nerve roots. CONCLUSION: The spinal fMRI method described enables large volume coverage of the spinal cord in three dimensions, with reliable and reproducible results.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".