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Record W2246953049

Investigations of Child Pedestrians or Cyclists Stuck by Motor Vehicles

2010· article· en· W2246953049 on OpenAlexaboutno aff
Linda Rothman, Lee Lee

Bibliographic record

VenueInjury Prevention · 2010
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsnot available
Fundersnot available
KeywordsPedestrianCrashCollisionInjury preventionPoison controlHuman factors and ergonomicsMotor vehicle crashOccupational safety and healthSuicide preventionTransport engineeringMedical emergencyEngineeringForensic engineeringMedicinePsychologyComputer securityComputer science
DOInot available

Abstract

fetched live from OpenAlex

This study describes how collisions involving child pedestrians and cyclists represent a large injury burden for Canadians less than 14 years of age. Although motor vehicle collision studies investigating occupants and their injuries are well-established, collisions involving child pedestrians/cyclists have not been reconstructed in this manner. The purpose of this study was to develop a methodology for the investigation of child cyclist and pedestrian collisions in order to reconstruct crash events based on data at the scene and medical assessment in the hospital, and also to discuss potential countermeasures. Children aged 4-15 were included in the study if they were a pedestrian or cyclist involved in a collision with a motor vehicle and as a result, were admitted to the Hospital for Sick Children (HSC) in Toronto, Canada or stayed in the emergency department for over 12 hours between July 2007 and October 2008. Crash scene investigations were performed by a collision investigator in collaboration with the Toronto Police Traffic Services Division. Medical trauma data collection was done via the child’s medical charts at the HSC. The study shows how three child pedestrian and one child cyclist versus motor vehicle collisions were successfully reconstructed. Mechanisms of injury were determined. Investigations of child pedestrian and cyclist versus motor vehicle collisions provide useful insights regarding injury profiles and countermeasures. There were numerous inadequacies in the built-environment that set the stage for these collisions. The focus of countermeasures for prevention of child pedestrian and cyclist injuries should be directed at the built environment.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score0.323

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 head0.008
GPT teacher head0.240
Teacher spread0.232 · 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 designBench or experimental
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
Published2010
Admission routes1
Has abstractyes

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