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Record W2199788296 · doi:10.4271/2004-01-0737

Door Latch Vulnerability to Rollover Induced Loads

2004· article· en· W2199788296 on OpenAlexaff
Andrew Gilberg, Jeremy Buckingham, Richard H. McSwain, Dirk Paulitz, Mark Hood

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2004
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsTekna Plasma Systems (Canada)
Fundersnot available
KeywordsRollover (web design)Vulnerability (computing)Computer scienceAutomotive engineeringElectrical engineeringComputer securityEngineering

Abstract

fetched live from OpenAlex

Light truck and SUV rollovers often involve ground contacts at the roof rails or door sills that can induce significant vertical shear loads at the latch/striker interface. These vertical loads are not evaluated in Federal Motor Vehicle Safety Standard testing yet they are known to cause latch failures. Such failures expose both belted and unrestrained occupants to increased injury risk. An example of two such failures can be found in open literature in a single van rollover test. A simple vertical load test for latches is described by the authors and evaluated for discrimination, suitability and repeatability. This test was applied to an array of current and past generation latches found on many popular SUVs and light trucks. A large range of failure loads was encountered. A review of the structural features of the superior performing test samples suggests simple modifications that could dramatically improve performance of the remaining latches. Improved performance in this vertical load test could be expected to translate to fewer unwanted door openings and ejections in field accidents.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.022
GPT teacher head0.294
Teacher spread0.272 · 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 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

Citations3
Published2004
Admission routes1
Has abstractyes

Explore more

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