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Record W2000789361 · doi:10.1177/1541931214581462

EMG provides an earlier glimpse into the effects of cognitive distraction on brake motor response

2014· article· en· W2000789361 on OpenAlexaff
Pamela D’Addario, Birsen Donmez, Kurt W. Ising

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2014
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDistractionBrakeCognitionPerceptionElectromyographyPhysical medicine and rehabilitationStimulus (psychology)PsychologyAudiologyVigilance (psychology)Cognitive psychologyMedicineEngineeringAutomotive engineeringNeuroscience

Abstract

fetched live from OpenAlex

A driver’s ability to quickly perceive and respond to hazards is critical for traffic safety. With limited cognitive resources, any added distractions are likely to increase response times. This study analyzed the effect of two cognitive distraction tasks, 1-back and countdown, on total brake-response time and its subcomponents: perception and leg movement times (n=6). Participants sat in a stationary vehicle and responded to a light stimulus by moving their foot from the accelerator to the brake pedal as quickly as possible. Electromyography (EMG) recordings of the lower leg muscle provided earlier detection of movement onset compared to accelerator pedal motion. Performing a cognitive task was found to increase perception and total brake-response time compared to the baseline condition. There were no significant differences observed in leg movement time while performing either of the distraction tasks versus the baseline. Implications for areas of improvement and future works are discussed.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.807
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.292
Teacher spread0.280 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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