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Record W2032411060 · doi:10.1016/s0304-3959(03)00297-5

Effects of odors on pain perception: deciphering the roles of emotion and attention

2003· article· en· W2032411060 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePain · 2003
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchNational Institutes of HealthMcGill University
KeywordsPsychologyValence (chemistry)OdorAnxietyMoodPerceptionAffect (linguistics)ArousalNociceptionPain perceptionCognitive psychologyAudiologyNeuroscienceClinical psychologyMedicineCommunicationPsychiatryAnesthesia

Abstract

fetched live from OpenAlex

Emotions have been shown to alter pain perception, but the underlying mechanism is unclear since emotions also affect attention, which itself changes nociceptive transmission. We manipulated independently direction of attention and emotional state, using tasks involving heat pain and pleasant and unpleasant odors. Shifts in attention between the thermal and olfactory modalities did not alter mood or anxiety. Yet, when subjects focused attention on the pain, they perceived it as clearly more intense and somewhat more unpleasant than when they attended to the odor. In contrast, odor valence altered mood, anxiety level, and pain unpleasantness, but did not change the perception of pain intensity. Pain unpleasantness ratings correlated with mood, but not with odor valence, suggesting that emotional changes underlie the selective modulation of pain affect. These results show that emotion and attention differentially alter pain perception and thus invoke at least partially separable neural modulatory circuits.

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)0.002
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 score0.288
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.239
Teacher spread0.189 · 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