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Record W4403935499 · doi:10.1016/j.sctalk.2024.100403

Exploring fundamentals of immersive environment setups on food sensory perception in space contexts

2024· article· en· W4403935499 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience Talks · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSensory Analysis and Statistical Methods
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPerceptionSpace (punctuation)Sensory systemHuman–computer interactionComputer sciencePsychologyCognitive psychologyNeuroscience

Abstract

fetched live from OpenAlex

Research suggests that space travel alters sensory perception, however, it is not yet clear what individual factors affect this perception. Taylor et al. (2020) emphasised the importance of tailoring strategies to enhance palatability and intake based on individual differences. This study aims to evaluate how an immersive space-like environment, created using screens, influences food odour perception and emotional responses. Specifically, it explores the setup of immersive screen studies to assess sensory perception and affective responses over time, considering factors such as lighting conditions in dark versus bright rooms. 29 participants were involved in a crossover design experiment in which they watched a 20-min video of a rocket launch, accompanied by environmental sounds at 70 dB, following NASA's International Space Station noise constraints. The participants were randomly assigned to evaluate the video in either a dark or bright room. The rocket launch video was chosen for its emotional impact, as it can induce awe and self-transcendent experiences, like the “Overview Effect” experienced by astronauts. Participants assessed the intensity of three food odours (vanilla, citrus, and almond) at four time points: just after takeoff, and at 5, 10, and 15 min. Measurements included liking (9-point hedonic scale), intensity (Labeled Magnitude Scale), and emotional responses (using 39 terms from the EsSense Profile). Results showed that for vanilla and almond, odour liking remained consistent over time, regardless of lighting conditions. However, for citrus, liking increased over time in the dark room. An inverse relationship between positive and negative emotions throughout the immersion period was observed, highlighting the importance of time in evoking emotional responses. Emotions during testing with the immersive screens were generally positive, such as feelings of ‘calm’, suggesting that the methodology may not be entirely suitable for simulating the more cluttered and isolated environment of a space shuttle.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.667
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.154
GPT teacher head0.308
Teacher spread0.153 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it