Exposure to a pleasant odour may increase the sense of reality, but not the sense of presence or realism
Bibliographic record
Abstract
Smell can increase the sense of presence, reality, and realism when exposed in a virtual environment. This effect has been found to be increased when the nature of the odour is concordant visually with the scene, i.e. exposure to an unpleasant odour in a filthy virtual kitchen. The objective of this project was to verify whether this effect could be generalised to pleasant odours. Participants were immersed in a virtual apartment with a kitchen where the visual scene suggested that cinnamon apple pies had recently been baked. Participants were randomly and blindly assigned to three conditions: exposition to the ambient air, to a pleasant odour of cinnamon apple pie, or an unpleasant odour of urine. The results indicated that while exposure to the visually concordant pleasant odour did increase the sense of reality in a statistically significant manner, it did not affect the sense of presence or realism. Results also suggested that the visual/olfactory concordance may have facilitated the detection of the pleasant odour. The potential implications of the results, potential explanations for the lack of effect on the sense of presence, as well as potential follow-up research projects are discussed.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".