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Record W2038232507 · doi:10.1177/154193120605001805

Usability Study of the Universal Anchorage System (UAS) for Child Restraint Systems (CRS) in School Buses and Passenger Vehicles

2006· article· en· W2038232507 on OpenAlexaffabout
Andrea Scipione, Joe Armstrong, Gerald Lai, Alice Salway, Jason Kumagai, Christina M. Rudin-Brown

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2006
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsTransport Canada
Fundersnot available
KeywordsUsabilityTransport engineeringComputer scienceEngineeringAeronauticsHuman–computer interaction

Abstract

fetched live from OpenAlex

There have been no usability studies assessing the new Child Restraint System (CRS) Universal Anchorage System (UAS) since the system's implementation in Canada in 2002. A Within-Subjects design research study involving forty-eight participants was conducted to evaluate how effectively users installed CRSs within a vehicle and a school bus when using different Lower Anchorage Connector (LAC) and Top Tether designs. The research indicates that users are not familiar with the UAS, and that safe installation of CRSs when using the UAS is not intuitive, resulting in significant installation safety errors. Furthermore, CRS users do not understand the severity of their installation errors, and the impact these errors have on compromising child safety. Industry and Regulators must increase UAS awareness, to inform users of the new UAS design and its components, and how the UAS impacts correct and safe CRS installation.

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)0.012
metaresearch head score (Gemma)0.032
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 score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.236
Teacher spread0.221 · 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

Citations0
Published2006
Admission routes2
Has abstractyes

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Same venueProceedings of the Human Factors and Ergonomics Society Annual MeetingSame topicAutomotive and Human Injury BiomechanicsFrench-language works237,207