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Record W2588801768

Electrophysiological correlates of inattentional deafness:
\nno hearing without listening

2012· preprint· en· W2588801768 on OpenAlexaff
Louise Giraudet, Marie-Eve Saint-Louis, Mickaël Causse

Bibliographic record

VenueOpen Archive Toulouse Archive Ouverte (University of Toulouse) · 2012
Typepreprint
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsInattentional blindnessPsychologyElectroencephalographyPerceptionCognitive psychologyAudiologyActive listeningContext (archaeology)Stimulus (psychology)CommunicationMedicineNeuroscience
DOInot available

Abstract

fetched live from OpenAlex

The analysis of airplane accidents reveals that pilots sometimes purely fail to notice yet critical auditory alerts. This inability of an auditory stimulus to reach consciousness has been recently coined under the term of inattentional deafness. Recent data from literature tend to show that tasks involving high perceptual load consume most of attentional capacity, leaving little for processing any taskirrelevant information. In addition, there is a growing body of evidence for a shared attentional capacity between vision and hearing. In this context, the numerous displays in cockpits are likely to produce inattentional deafness. A simplified piloting task was conceived, in which participants were required to make decisions based on complex visual indicators while continuous electroencephalographic(EEG) measurements were performed. During the task, a tone was played, either standard, which participants were told to ignore, or deviant (“the alarm”, probability = 0.10) which participants were told to report. Preliminary behavioural results showed that up to 30% of deviant sounds were not detected. The analysis of EEG showed that a drastic diminution of the auditory P300 amplitude was concomitant with the occurrence of the inattentional deafness phenomenon. Applications concern integrative online prevention of alarms omission, mental workload measurements and enhanced warning designs.

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), Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0040.011
Research integrity0.0000.002
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 head0.039
GPT teacher head0.262
Teacher spread0.223 · 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

Citations10
Published2012
Admission routes1
Has abstractyes

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