Default network correlations analyzed on native surfaces
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
Disruptions of interregional correlations in the blood oxygenation level dependent fMRI signal have been reported in multiple diseases, including Alzheimer's disease and mild cognitive impairment. "Default network" regions that overlap with areas of earliest amyloid deposition have been highlighted by these reports, and abnormal default network activity is also observed in unimpaired elderly subjects with high amyloid burden. However, one limitation of current methods for analysis of interregional correlations is that they rely on transformation of functional data to an atlas volume (e.g., Talairach-Tournoux or Montreal Neurological Institute atlases) and may not adequately account for anatomic variation between subjects, particularly in the presence of atrophy. We assessed the utility of the FreeSurfer cortical parcellation to analyze default network functional correlations on the native surfaces of individual subjects. Group-level quantitative analysis was accomplished by comparing correlations between equivalent structures in different subjects. The method was applied to resting-state fMRI data from young, healthy subjects; preliminary results were also obtained from cognitively unimpaired elderly subjects and patients with Alzheimer's disease, Parkinson's disease, Parkinson's disease dementia, and dementia with Lewy bodies.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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