Psychoneuroendocrine protocol to comprehensively study sexually dimorphic cognition
Bibliographic record
Abstract
Background: A large body of research provides evidence for sex differences in cognitive abilities. These sex differences stem from the interplay between biological sex (e.g., birth-assigned sex, sex hormones) and psychosocial gender (e.g., gender identity, gender-roles, sexual orientation). Literature remains rather mixed with regards to the magnitude of sex and gender effects on cognitive abilities and mental health. Growing evidence shows that sex hormone assessment combined with measures of psychosocial gender may be fundamental to comprehensively understand individual differences in sexually dimorphic cognitive abilities. Objectives: This study protocol describes a sexually dimorphic cognitive battery to assess the influence of sex hormones on performance. In parallel, we aim to assess the inter-related effects that biological sex and psychosocial gender-based factors exert on cognition and mental health. Methods: Our projected sample includes 180 adult participants who are at least 18 years old. Sub-groups will be recruited based on birth-assigned sex, gender identity, and sexual orientation. Biological measures will be collected via salivary samples throughout testing to include sex hormones (testosterone, estradiol and progesterone) and stress hormones (cortisol). Demographic and psychosocial variables will be measured through self-report questionnaires. Participants will be required to complete eight classic cognitive tasks that assess a variety of cognitive domains in a 2-h testing session. Results and future directions: Results from this study provides unique insights into the correlates of cognitive sex differences and gender diversity. This will give us solid ground to further investigate these influences in clinical populations in which sex hormones and cognitive functioning are often altered.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.113 | 0.034 |
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".