Gender Related Differences in the Possible Effect of Simian Crease on Alexithymia Scores in University Students
Bibliographic record
Abstract
Background: The simian crease is a single line on the palm. Normal healthy people can have it on their one or both palms, but it can be seen in persons with different pathologies such as Down’s syndrome, leukemia, Alzheimer’s disease, and some behavioral problems. \n \nMethods: Fifty-seven Nigerian university students participated to the study. Participants were 38 men and 19 women who were 18-24 years of age. To get their alexithymia scores were used the Toronto Alexithymia Scale. \n \nResults: There were no simian crease status-related statistically significant differences in alexithymia scores in the total sample, in male and in female subjects. However, there were statistically significant gender-related differences in total sample (t=2.128, p=0.038) and in subjects with simian crease (t=2.551, p=0.016), but not in subjects without simian crease. \n \nDiscussion: Gender related differences in the possible effect of simian crease on alexithymia scores in university students in the present study, the increased alexithymia scores in women compared to men in the normal population suggest that simian crease may be an important congenital or genetic factor in the pathogenesis of some psychologic abnormalities including depression and alexithymia, especially in women. \n \nConclusion: Therefore, the simian crease status can be taken into consideration in the diagnosis and clinical follow-up of alexithymia, especially in women
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.006 | 0.001 |
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".