White Matter Microstructure Among Straight and Gay Cisgender Men, <i>Sao Praphet Song</i>, and Straight Cisgender Women in Thailand
Bibliographic record
Abstract
White matter (WM) microstructure is differentiated in relation to sex/gender, psychosexuality, and, among transgender people, gender-affirming hormone (GAH) use. Prior research focused on Western samples, which limits generalizability to other populations. Here, diffusion tensor imaging (DTI) was used to assess WM microstructure in a Thai sample (N = 128) of straight cisgender men, straight cisgender women, gay cisgender men, and sao praphet song (i.e., transfeminine individuals assigned male at birth and sexually attracted to cisgender men). Sao praphet song were further grouped by GAH use. Groups were compared on fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) using whole-brain tract-based spatial statistics (TBSS). FA, AD, and RD were further examined via multivariate analysis to assess covariance across WM microstructural indices and participant groups. A significant multivariate pattern differentiated the feminine- from masculine-identifying groups irrespective of sex assigned at birth and suggested WM tissue organization was greater among the latter in the bilateral cingulum, anterior corona radiata, left corpus callosum, and right superior longitudinal fasciculus, forceps minor, and corticospinal tracts. TBSS analyses reinforced that WM differed by gender identity in various regions. Among sao praphet song, GAH use was associated with lower regional FA, suggesting less WM organization bilaterally in the corpus callosum, cingulum, and anterior corona radiata. The findings aligned with prior studies in Western samples, indicating cross-population generalizability of WM microstructural differentiation in relation to sex/gender, psychosexuality, and GAH use.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".