Using the Dual Control Model to Investigate the Relationship Between Mood, Genital, and Self-Reported Sexual Arousal in Men and Women
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent findings suggest that there is considerable interindividual variability in how mood affects sexual arousal and that the dual control model may be helpful in explaining this variation. The current research investigated whether mood interacted with sexual excitation and inhibition proneness to predict subjective and genital arousal. In this study, 33 participants (18 men; 15 women), ages 18 to 45, attended three laboratory sessions where they completed questionnaires assessing preexisting mood and propensity for sexual excitation and inhibition, then watched a series of neutral and sexually explicit films. Subjective sexual arousal was continuously indicated during each film, while genital temperature was measured using thermographic imaging. Sexual excitation and inhibition interacted with various mood scores to significantly predict both subjective and genital arousal in men and women. Several gender differences were found. For example, vigor scores interacted with sexual excitation proneness to significantly predict genital but not subjective arousal in women, while the same interaction significantly predicted subjective but not genital arousal in men. The findings supported the hypothesis that the dual control model is an important framework in understanding how mood influences both subjective and genital sexual arousal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.002 |
| 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 | 0.001 |
| 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 it