Odor Localization and Sniffing
Bibliographic record
Abstract
For humans, the localization of an odorant seems only possible if the odorant also stimulates the trigeminal nerve. There is, however, some evidence that active sniffing may affect this ability and facilitate the localization of pure odorants. Therefore, we tested the ability of 40 subjects to localize a pure odorant and a mixed olfactory/trigeminal stimulus under 2 stimulation conditions: either odors were blown into the subjects' nostrils (passive) or subjects had to actively sniff the odors (active). Subjects could only reliably localize the mixed olfactory/trigeminal stimulus. However, we found a significant interaction between stimulation condition and nature of the odorant. So, the mixed olfactory/trigeminal stimulus was more localizable in the passive condition, whereas the pure odorant was better localized in the active condition. Interestingly, subjects had more correct answers after stimulation of the right nostril than of the left nostril (where subjects performed significantly below chance when stimulated with the pure odorant), suggesting possible laterality effects. These results suggest that active sniffing may affect our ability to localize odors. Other than mixed olfactory trigeminal stimuli, pure odorants are, however, not localizable even in active condition of sniffing.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".