MétaCan
Menu
Back to cohort
Record W2025387799 · doi:10.1115/imece2002-32634

Pediatric Airbag Injuries

2002· article· en· W2025387799 on OpenAlexaboutno aff
Anthony Sances, Srirangam Kumaresan, David L. Daniels, Keith Friedman

Bibliographic record

VenueAdvances in Bioengineering · 2002
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsnot available
Fundersnot available
KeywordsAirbagCrashMedicineInjury preventionPoison controlOccupational safety and healthMedical emergencyAutomotive engineeringEngineeringComputer science

Abstract

fetched live from OpenAlex

The advent of airbag technology has helped to reduce the injuries to belted occupants in motor vehicles during moderate to severe frontal and near frontal crashes [1–3]. Airbags have been in use since the early 1970s. As of July 2001, airbags have saved 7224 lives including 6066 drivers and 1158 front right passengers. However, the airbag deployments at low crash severity showed higher injury probability of occupants. The majority of airbag fatalities are associated with low speed impacts with deployments. As of July 2001, the National Highway Traffic Safety Administration (NHTSA) has reported 144 fatalities and serious life threatening injuries to children due to passenger airbags [4]. It is also reported that four children died and one child sustained life-threatening injury due to a driver side airbag. The publication from Transport Canada noted that the airbags increase the overall risk of injury of children under the age of 10 by approximately 21% [5]. Although the airbags have saved many lives, they are also responsible for fatalities and serious injuries during low speed severity collision. The present study reports pediatric airbag injuries sustained during low speed crashes.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score0.453

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 head0.013
GPT teacher head0.258
Teacher spread0.245 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in BioengineeringSame topicAutomotive and Human Injury BiomechanicsFrench-language works237,207