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Record W404861059

Effect of Old Age on Dual Task Performance During Driving Simulations of Varying Complexities

2006· article· en· W404861059 on OpenAlex
Andrée-Ann Cyr, Stéphanie Yamin, Alexandre Bélanger, Malcolm Man-Soon Hing, Shawn Marshall, Sylvain Gagnon

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in transportation studies · 2006
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTask (project management)Dual (grammatical number)CognitionDriving simulatorEvent (particle physics)Cognitive loadPsychologyAge groupsPoison controlSimulationComputer scienceEngineeringMedicineMedical emergencyDemographyPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

The authors study how, in a simulated environment, cognitive load is affected by age and road events. In a STISIM driving simulator, 15 older and 15 young adults were exposed to 4 scenarios, including roadway events, that were: 1) free driving (normal), 2) turns (complex) and 3) car incursion (unexpected). Dual-task reaction time and detection accuracy with NASA-TLX ratings were used to assess event-generated cognitive load. Study results show that while facing unexpected and complex road events, young adults showed lower NASA-TLX ratings and shorter dual task reaction times than older adults. Results show that understanding older driver roadway event reaction using the cognitive load approach is valid.

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.

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 score0.467
Threshold uncertainty score0.474

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)0.0000.000

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 head0.021
GPT teacher head0.379
Teacher spread0.358 · 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