Oxytocin modulates human chemosensory decoding of sex in a dose-dependent manner
Bibliographic record
Abstract
There has been accumulating evidence of human social chemo-signaling, but the underlying mechanisms remain poorly understood. Considering the evolutionarily conserved roles of oxytocin and vasopressin in reproductive and social behaviors, we examined whether the two neuropeptides are involved in the subconscious processing of androsta-4,16,-dien-3-one and estra-1,3,5 (10),16-tetraen-3-ol, two human chemosignals that convey masculinity and femininity to the targeted recipients, respectively. Psychophysical data collected from 216 heterosexual and homosexual men across five experiments totaling 1056 testing sessions consistently showed that such chemosensory communications of masculinity and femininity were blocked by a competitive antagonist of both oxytocin and vasopressin receptors called atosiban, administered nasally. On the other hand, intranasal oxytocin, but not vasopressin, modulated the decoding of androstadienone and estratetraenol in manners that were dose-dependent, nonmonotonic, and contingent upon the recipients' social proficiency. Taken together, these findings establish a causal link between neuroendocrine factors and subconscious chemosensory communications of sex-specific information in humans.
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.
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 | 0.000 |
| 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) | 0.002 | 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".