The neuronal substrates of human olfactory based kin recognition
Bibliographic record
Abstract
Kin recognition, an evolutionary phenomenon ubiquitous among phyla, is thought to promote an individual's genes by facilitating nepotism and avoidance of inbreeding. Whereas isolating and studying kin recognition mechanisms in humans using auditory and visual stimuli is problematic because of the high degree of conscious recognition of the individual involved, kin recognition based on body odors is done predominantly without conscious recognition. Using this, we mapped the neural substrates of human kin recognition by acquiring measures of regional cerebral blood flow from women smelling the body odors of either their sister or their same-sex friend. The initial behavioral experiment demonstrated that accurate identification of kin is performed with a low conscious recognition. The subsequent neuroimaging experiment demonstrated that olfactory based kin recognition in women recruited the frontal-temporal junction, the insula, and the dorsomedial prefrontal cortex; the latter area is implicated in the coding of self-referent processing and kin recognition. We further show that the neuronal response is seemingly independent of conscious identification of the individual source, demonstrating that humans have an odor based kin detection system akin to what has been shown for other mammals.
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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 | 0.000 |
| 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) | 0.001 | 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".