MétaCan
Menu
Back to cohort
Record W2081799624 · doi:10.1177/154193120605002205

The Occlusion Procedure for Assessing in-Vehicle Telematics: Tests of Current Vehicle Systems

2006· article· en· W2081799624 on OpenAlexaff
Joanne L. Harbluk, Peter C. Burns, Eun-kyoung Go, Amanda Morton

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2006
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsTransport Canada
Fundersnot available
KeywordsDistractionTelematicsComputer scienceTask (project management)Human–computer interactionEngineeringSystems engineeringPsychology

Abstract

fetched live from OpenAlex

Appropriate protocols are necessary for assessing the distraction potential of in-vehicle tasks and devices. The AAM (Alliance of Automobile Manufacturers) has proposed the “Statement of Principles, Criteria and Verification Procedures on Driver Interactions with Advanced In-Vehicle Information and Communication Systems” (AAM, 2003). The purpose of the present study was to assess the utility of one specific method, the Occlusion Method (as outlined by Principle 2.1 of the AAM Guidelines) by applying it to four navigation systems available in current production vehicles. This method was used to assess the distraction potential for 16 participants as they completed navigation-related tasks involving visual display and manual controls. The results provide evidence that the Total Shutter Open Time (TSOT) measure from the Occlusion Task is a promising method for discriminating between different task types and complexity levels of these tasks as well as between different telematics systems.

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)0.000
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 score0.070
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.025
GPT teacher head0.323
Teacher spread0.299 · 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
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Human Factors and Ergonomics Society Annual MeetingSame topicHuman-Automation Interaction and SafetyFrench-language works237,207