Neuroanthropology: Olfactory Recognition of the Self / Non-self by the Ancestral MHC: An EEG Study
Bibliographic record
Abstract
Humans naturally discriminate between different ethnic group members using visual and other sensory information, including the sense of smell. The genetic diversity of humans serves as biological and social sign stimuli in the neural self/non-self recognition process. As already evident, the major histocompatibility complex (MHC) encodes both an individual self and a shared ancestral self into the body odor. In a pilot study, we examine the brain-evoked responses to ancestral encoded body odors by conducting an olfactory EEG recording of four different groups: Germans, Taiwanese, Koreans, and Chinese. Results show that humans recognize in-group members as familiar and they exhibit practically identical rhythmic EEG patterns to one’s own odor as it pertains to the ancestral in-group odors. This reveals their genetic relatedness. It is hereby demonstrated that shared ethnicity results in behaviors (both group-protective and pro-social) that are important to intra- and inter-group dynamics.
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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) | 0.002 | 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".