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Record W2118000934 · doi:10.1007/s10548-009-0099-0

Instrumental Music Influences Recognition of Emotional Body Language

2009· article· en· W2118000934 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

VenueBrain Topography · 2009
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsUniversité de MontréalInternational Laboratory for Brain, Music and Sound Research
Fundersnot available
KeywordsPsychologySadnessCategorizationStimulus modalityHappinessCognitive psychologyCrossmodalStimulus (psychology)Modality (human–computer interaction)ModalitiesEveryday lifeSensory systemPerceptionVisual perceptionLinguisticsSocial psychologyComputer scienceAnger

Abstract

fetched live from OpenAlex

In everyday life, emotional events are perceived by multiple sensory systems. Research has shown that recognition of emotions in one modality is biased towards the emotion expressed in a simultaneously presented but task irrelevant modality. In the present study, we combine visual and auditory stimuli that convey similar affective meaning but have a low probability of co-occurrence in everyday life. Dynamic face-blurred whole body expressions of a person grasping an object while expressing happiness or sadness are presented in combination with fragments of happy or sad instrumental classical music. Participants were instructed to categorize the emotion expressed by the visual stimulus. The results show that recognition of body language is influenced by the auditory stimuli. These findings indicate that crossmodal influences as previously observed for audiovisual speech can also be obtained from the ignored auditory to the attended visual modality in audiovisual stimuli that consist of whole bodies and music.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0100.000

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 head0.038
GPT teacher head0.332
Teacher spread0.294 · 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