Functional MRI of the brain stem for assessing its autonomic functions: from imaging parameters and analysis to functional atlas
Bibliographic record
Abstract
We provided the dataset of pre-processed anatomic and functional brain MR images from 10 healthy controls. The dataset can be used to replicate the results of the manuscript titled 'Functional MRI of the brain stem for assessing its autonomic functions: from imaging parameters and analysis to functional atlas.' This manuscript presented an optimised functional imaging brainstem imaging protocol (FIBS). Skulls were removed from the shared MRI images, and brain images were normalised to the Montreal Neurological Institute (MNI) space to protect participants' privacy. Details of pre-processing were provided in the paper mentioned above. The atlas includes 12 regions of interest (ROIs) in the brain stem involving automatic controls. This dataset could potentially be used to: 1. compare temporal signal-to-noise ratios among different imaging protocols; 2. provide the brain stem anatomic locations involved in autonomic controls; 3. add to the normal control database for brain stem studies.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.020 |
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".