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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".