A high-resolution 7 Tesla resting-state fMRI dataset optimized for studying the subcortex
Bibliographic record
Abstract
acquisition of intrinsic activity across both cortical and subcortical regions is necessary. Here we present advanced whole-brain, resting-state functional magnetic resonance imaging (rs-fMRI) data acquired at 7 Tesla with 1.5 mm isotropic voxel resolution. Functional images were obtained from 56 healthy adults (33 females, ages 19-39 years) in two runs of 15 min eyes-open wakeful rest. The high spatial resolution and short echo times of the multiband echo-planar imaging (EPI) protocol optimizes blood oxygen level-dependent (BOLD)-sensitivity for the subcortex while concurrent respiratory and cardiac measures enable retrospective correction of physiological noise, resulting in data that is highly suitable for researchers interested in subcortical BOLD signal. Functional timeseries were coregistered to high-resolution T1-weighted structural data (0.75 mm isotropic voxels) acquired during the same scanning session. To accommodate data reutilization, functional and structural images were formatted to the Brain Imaging Data Structure (BIDS) and preprocessed with fMRIPrep.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".