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Record W2014237282 · doi:10.3357/asem.2383.2009

Stimulus Complexity and Dual Tasking Effects on Sustained Auditory Attention in Noise

2009· article· en· W2014237282 on OpenAlexaff
Sharon M. Abel

Bibliographic record

VenueAviation Space and Environmental Medicine · 2009
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsStimulus (psychology)AudiologyNoise (video)Dichotic listeningVigilance (psychology)Speech recognitionPsychologyStimulus onset asynchronyTask (project management)CommunicationComputer scienceCognitive psychologyCognitionNeuroscienceMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

INTRODUCTION: The effect on sustained auditory attention of a constellation of factors that characterize aviation, maritime, and land environments was investigated. The ability to detect infrequent spoken messages while performing an unrelated visual motor tracking task was studied in the presence of background noise. METHOD: Six subjects each were assigned to four conditions defined by the presence/absence of 80-dBA pink noise and presence/absence of the secondary task. Subjects were given three detection tests in which the 75-dB SPL critical signal was comprised of one, two, or three components. A button press with the left hand signified detection of the critical signal. For each test there were six consecutive 20-min vigils comprised of 150 trials. The critical signal was presented in 10 of these. For the tracking task subjects used a computer mouse controlled by the right hand to follow the sinusoidal movement of a 3-cm vertical line across a computer monitor. RESULTS AND CONCLUSIONS: Background noise resulted in a significant decrease in hits, and significant increases in false alarms and response time. Since the signal and noise were both auditory, the noise was likely effective as a masker rather than a stressor. The secondary task did not impact performance, possibly because the auditory task was too easy and the event rate too slow. As in previous studies using alphanumeric events, there was no attention decrement over time. However, response time decreased as the number of components in the critical signal increased. Possible explanations are guided attention through priming or the provision of a temporal foreperiod.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score0.781

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)0.0010.000

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 head0.014
GPT teacher head0.303
Teacher spread0.289 · 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.

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

Citations5
Published2009
Admission routes1
Has abstractyes

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