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Record W2085238083 · doi:10.1037/1076-898x.14.3.201

Evaluating warning sound urgency with reaction times.

2008· article· en· W2085238083 on OpenAlexaff
Clara Suied, Patrick Susini, Stephen McAdams

Bibliographic record

VenueJournal of Experimental Psychology Applied · 2008
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsALARMArousalContext (archaeology)Computer scienceInterval (graph theory)Sound (geography)Pulse (music)Speech recognitionPsychologyCognitive psychologyAcousticsSocial psychologyEngineeringMathematics

Abstract

fetched live from OpenAlex

It is well-established that subjective judgments of perceived urgency of alarm sounds can be affected by acoustic parameters. In this study, the authors investigated an objective measurement, the reaction time (RT), to test the effectiveness of temporal parameters of sounds in the context of warning sounds. Three experiments were performed using a RT paradigm, with two different concurrent visuomotor tracking tasks simulating driving conditions. Experiments 1 and 2 show that RT decreases as interonset interval (IOI) decreases, where IOI is defined as the time elapsed from the onset of one sound pulse to the onset of the next. Experiment 3 shows that temporal irregularity between pulses can capture a listener's attention. These findings lead to concrete recommendations: IOI can be used to modulate warning sound urgency; and temporal irregularity can provoke an arousal effect in listeners. The authors also argue that the RT paradigm provides a useful tool for clarifying some of the factors involved in alarm processing.

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)0.003
metaresearch head score (Gemma)0.027
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 score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.027
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.158
GPT teacher head0.522
Teacher spread0.363 · 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

Citations88
Published2008
Admission routes1
Has abstractyes

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