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Record W3108536367 · doi:10.1177/0963721420964175

What Your Nose Knows: Affective, Cognitive, and Behavioral Responses to the Scent of Another Person

2020· article· en· W3108536367 on OpenAlexaff
Marlise K. Hofer, Frances S. Chen, Mark Schaller

Bibliographic record

VenueCurrent Directions in Psychological Science · 2020
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
Fundersnot available
KeywordsPsychologyCognitionAffect (linguistics)Impression formationCognitive psychologySocial psychologyCommunicationSocial perceptionPerceptionNeuroscience

Abstract

fetched live from OpenAlex

People readily perceive and react to the body odors of other people, which creates a wide range of implications for affective, cognitive, and behavioral responses. In this article, we provide an overview of recent research in this area. We summarize the process by which people associate body odors with different kinds of interpersonally relevant information, briefly review two lines of research on responses to strangers’ body odors (research on olfactory cues and emotions, research on olfactory cues and impression formation), and review new research on the psychological consequences of smelling loved ones’ odors—including consequences for stress reduction and sleep enhancement. We conclude with a discussion of emerging research questions and methodological considerations that may help guide future inquiry into the various ways that the odors of other people influence one’s emotions, cognitions, relationships, and health.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.794
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.424
GPT teacher head0.454
Teacher spread0.030 · 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 designObservational
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

Citations19
Published2020
Admission routes1
Has abstractyes

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