Demographic and geographical determinants of human olfactory perception of 909 individuals inhabiting 16 regions
Bibliographic record
Abstract
The hedonic perception of odors is similar worldwide. However, our perception of smells is much more than just determining whether an odor is pleasant or not. Here, we expanded this assessment by recruiting 909 people from 16 regions of the world and measuring 12 perceptual dimensions (e.g., pleasantness, intensity, edibility), which were aggregated into an olfactory perceptual fingerprint. We used two fingerprints: descriptor-specific and odor-specific. Age, gender, and region explained 1.1%, 0.3%, and 9.6% of variance in the descriptor-specific fingerprints, respectively. Similarly, age, gender, and region explained 0.5%, 0.3%, and 8.2% of variance in the odor-specific fingerprints. Interestingly, odor intensity was more regionally dependent than pleasantness. Thus, olfactory perception across the globe may be better differentiated by odor intensity than pleasantness. Although there is some influence of individual and cultural backgrounds, human perception of odors appears to be quite similar worldwide, even when assessed using 12 perceptual dimensions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".