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Record W2128424237 · doi:10.1097/wnr.0b013e3282f1ab1d

The effect of visual reliability on auditory–visual integration: an event-related potential study

2007· article· en· W2128424237 on OpenAlexaff
Qiang Liu, Jiang Qiu, Antao Chen, Juan Yang, Qinglin Zhang, Hong‐Jin Sun

Bibliographic record

VenueNeuroreport · 2007
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsMcMaster University
Fundersnot available
KeywordsEvent-related potentialReliability (semiconductor)NeuroscienceAudiologyPsychologyElectroencephalographyMedicinePhysics

Abstract

fetched live from OpenAlex

To investigate the neural mechanisms of auditory-visual integration, we recorded event-related potentials during a word-identification task, in which the stimulus was presented in the auditory (A), visual (V), and in the auditory-visual (AV) modalities. The reliability of the visual information varied at the high-reliability (VH) and low-reliability (VL) levels in both the V and AV presentations. The modulation of sensory integrations owing to the variation of cue reliability was revealed in the format of the double-difference waveform generated by subtracting the difference waveform AVL-(A+VL) from the difference waveform AVH-(A+VH). The results demonstrated (i) the early modulation of the activity in the auditory and visual cortex; (ii) subsequent spatial-temporal sequence of activities mostly occurred in multisensory areas; and (iii) the timing of final outputs of AV integration at around 370-410 ms poststimulus.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.400
Teacher spread0.383 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2007
Admission routes1
Has abstractyes

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