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Record W2039833972 · doi:10.1177/154193120605002201

Novice and Experienced Driving Performance with Cell Phones

2006· article· en· W2039833972 on OpenAlexafffundabout
Susan Chisholm, J.K. Caird, Julie Lockhart, L. E. Teteris, Alison Smiley

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2006
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsUniversity of Calgary
FundersUniversity of Calgary
KeywordsPhoneApplied psychologyPedestrianDriving simulatorTask (project management)PsychologyPerceptionAeronauticsSimulationEngineeringAudiologyTransport engineeringMedicine

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the effect of cell phones on novice drivers and the implications that the results of the study may have on the graduated licensing (GDL) restrictions. Twenty Novices, with less than 6 months of driving experience, and 20 Experienced drivers, with more than 10 years of experience, participated in the study. Perception response time (PRT) to hazards and eye movement measures were analyzed to determine if decrements in driver performance resulted during traffic events compared to baseline responses when using either a cell phone or CD player in the University of Calgary Driving Simulator. Results showed longer PRTs for the Novice compared to Experienced drivers for the lead vehicle braking, pedestrian, and vehicle pull out events. During the CD task increased glances into the vehicle and decreased rearview mirror glances were found. Implications of this research for cell phone restrictions within graduated licensing programs 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 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)0.001
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.009
GPT teacher head0.246
Teacher spread0.237 · 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

Citations12
Published2006
Admission routes3
Has abstractyes

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