Cortical microstructural changes in schizophrenia spectrum disorders using quantitative T1 mapping
Bibliographic record
Abstract
Introduction: Cortical brain changes have long been established in schizophrenia spectrum disorders (SSD), with a particular involvement of frontal and temporal areas. However, most studies to date focused on macrostructural analyses, such as cortical volume, thickness, and surface area. Quantitative T1 imaging (qT1) provides a measure of microstructural tissue properties, corresponding mainly to myelination. Methods: Fourteen SSD patients and 7 healthy controls were recruited and underwent qT1 imaging using two different acquisition sequences, single and multi-echo qT1. Results: Compared to controls, SSD patients had a pronounced increase in qT1 values in frontal and temporal areas, while accounting for age and sex. However, this was only detected by the single echo qT1. Additionally, single echo qT1 was negatively modulated by sex in the SSD group, with females having lower qT1 values compared to their male counterparts. Discussion: These results suggest impaired myelination in the frontal and temporal cortices in SSD. Lastly, we highlight the importance of protocol selection as inter-protocol reliability is still a concern despite the quantitative protocols developed to overcome this limitation.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".