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Record W7054669776

Audiovisual processing of affective and linguistic prosody : an event-related fMRI study

2008· dissertation· en· W7054669776 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2008
Typedissertation
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsProsodyUtteranceEmotional prosodyTask (project management)Modality (human–computer interaction)ModalitiesDeep linguistic processing
DOInot available

Abstract

fetched live from OpenAlex

This study was designed to clarify some of the issues surrounding the nature of hemispheric contributions to the processing of emotional and linguistic prosody, as well as to examine the relative contribution of different sensory modalities in processing prosodic structures. Ten healthy young participants were presented with semantically neutral sentences expressing affective or linguistic prosody solely through the use of non-verbal cues (intonation, facial expressions) while undergoing tMRI. The sentences were presented under auditory, visual, as well as audio-visual conditions. The emotional prosody task required participants to identify the emotion of the utterance (happy or angry) and the linguistic prosody task required participants to identify the type of utterance (question or statement). Core peri-sylvian, frontal and occipital areas were activated bilaterally in all conditions suggesting that processing of affective and linguistic prosodic structures is supported by overlapping networks. The strength of these activations may, in part, be modulated by task and modality of presentation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.409
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.257
Teacher spread0.245 · 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.

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

Citations0
Published2008
Admission routes1
Has abstractyes

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