Humans and the Olfactory Environment: A Case of Gene-Culture Coevolution?
Bibliographic record
Abstract
As hunter-gatherers, humans used their sense of smell to identify plants and animals, to find their way within a foraging area, or to distinguish each other by gender, age, kinship, or social dominance. Because women gathered while men hunted, the sexes evolved different sensitivities to plant and animal odors. They also ended up emitting different odors. Male odors served to intimidate rival males or assert dominance. With the rise of farming and sedentism, humans no longer needed their sense of smell to find elusive food sources or to orient themselves within a large area. Odors now came from a narrower range of plants and animals. Meanwhile, body odor was removed through bathing to facilitate interactions in enclosed spaces. This new phenotype became the template for the evolution of a new genotype: less sensitivity to odors of wild plants and animals, lower emissions of male odors, and a more negative response to them. Further change came with the development of fragrances to reodorize the body and the home. This new olfactory environment coevolved with the ability to represent odors in the mind, notably for storage in memory, for vicarious re-experiencing, or for sharing with other people through speech and writing.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".