Default mode network connectivity as a predictor of post‐traumatic stress disorder symptom severity in acutely traumatized subjects
Bibliographic record
Abstract
OBJECTIVE: The goal of this study was to investigate the relationship between default mode network connectivity and the severity of post-traumatic stress disorder (PTSD) symptoms in a sample of eleven acutely traumatized subjects. METHOD: Participants underwent a 5.5 min resting functional magnetic resonance imaging scan. Brain areas whose activity positively correlated with that of the posterior cingulate/precuneus (PCC) were assessed. To assess the relationship between severity of PTSD symptoms and PCC connectivity, the contrast image representing areas positively correlated with the PCC was correlated with the subjects' Clinician Administered PTSD Scale scores. RESULTS: Results suggest that resting state connectivity of the PCC with the perigenual anterior cingulate and the right amygdala is associated with current PTSD symptoms and that correlation with the right amygdala predicts future PTSD symptoms. CONCLUSION: These results may contribute to the development of prognostic tools to distinguish between those who will and those who will not develop PTSD.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".