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Record W2523176472 · doi:10.1093/chemse/bjw098

Individual Differences in Verbal and Non-Verbal Affective Responses to Smells: Influence of Odor Label Across Cultures

2016· article· en· W2523176472 on OpenAlexaffabout
Camille Ferdenzi, Pauline Joussain, Bérengère Galadriel Digard, Lucie Luneau, Jelena Djordjevic, Moustafa Bensafi

Bibliographic record

VenueChemical Senses · 2016
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsPsychologyOdorPerceptionCognitive psychologyOlfactionAction (physics)Variation (astronomy)Social psychologyDevelopmental psychologyNeuroscience

Abstract

fetched live from OpenAlex

Olfactory perception is highly variable from one person to another, as a function of individual and contextual factors. Here, we investigated the influence of 2 important factors of variation: culture and semantic information. More specifically, we tested whether cultural-specific knowledge and presence versus absence of odor names modulate odor perception, by measuring these effects in 2 populations differing in cultural background but not in language. Participants from France and Quebec, Canada, smelled 4 culture-specific and 2 non-specific odorants in 2 conditions: first without label, then with label. Their ratings of pleasantness, familiarity, edibility, and intensity were collected as well as their psychophysiological and olfactomotor responses. The results revealed significant effects of culture and semantic information, both at the verbal and non-verbal level. They also provided evidence that availability of semantic information reduced cultural differences. Semantic information had a unifying action on olfactory perception that overrode the influence of cultural background.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.003
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.088
GPT teacher head0.312
Teacher spread0.224 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations68
Published2016
Admission routes2
Has abstractyes

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