In a dirty virtual room: exposure to an unpleasant odor increases the senses of presence, reality, and realism
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A recent study found that in a virtual room devoid of obvious visual cues linking visual and olfactory stimuli, exposure to an unpleasant odor (but not to a pleasant one) led to statistically significant increases in the sense of Presence. A second study obtained similar results when concordant visual cues linking the visual scene and pleasant odor were presented. Both studies also reported that neither exposure to an unpleasant or pleasant odor influenced the sense of Realism. However, in the second study, the sense of Reality was statistically significantly higher when participants were exposed to the pleasant odor (but not to the unpleasant one). The goal of the current (and third) study was to clarify these relationships in a virtual environment where the visual scene was linked to an unpleasant odor. To this end, 60 participants were immersed in a filthy virtual kitchen, unaware of the potential exposure to an olfactory stimulus. Depending on their experimental condition, they were exposed to either the ambient odor in the laboratory, a pleasant odor, or an unpleasant odor. The results revealed that exposure to the unpleasant odor increased the senses of Presence and of Reality in a statistically significant manner. Furthermore, the results regarding odor detection rates suggest that visual/olfactory concordance may have facilitated the detection of the unpleasant odor. Overall, the results suggest that, in the case of an unpleasant odor, visual/olfactory concordance can notably enrich the quality of the user experience in virtual reality.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it