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Record W2261171521 · doi:10.4271/2000-01-3522

Trailer Underride Protection - A Canadian Perspective

2000· article· en· W2261171521 on OpenAlexafffundabout
Denis Boucher, Daniel B. T. Davis

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2000
Typearticle
Languageen
FieldEngineering
TopicSafety Systems Engineering in Autonomy
Canadian institutionsTransport Canada
FundersTransport Canada
KeywordsTrailerPerspective (graphical)Computer scienceComputer networkArtificial intelligence

Abstract

fetched live from OpenAlex

This paper provides details on the tests performed and the research findings of an underride guard test programme, including 10 full scale crashes using three types of deformable guards. The deformable guards tested included one meeting the minimum requirements of the NHTSA FMVSS 223 with ground clearances of either 560 or 480 mm, a second meeting the same minimum performance criteria with the addition of a device to limit the displacement of the horizontal member (ground clearance of 480 mm only) and a third being stiffer and designed to roughly maintain its 560 mm ground clearance during deformation. Crash tests were performed at speeds of 48, 56 and 65 kph. The tests showed that an underride guard built to the minimum requirements currently specified in FMVSS 223, could not provide adequate protection to occupants in a compact or sub-compact vehicle; in our tests, such a guard failed to stop a 1998 Honda Civic CX striking the guard at 56 km/h, resulting in the failure of the neck of the ATD sitting in the driver and front passenger positions. The tests also showed that lowering the guard height, increasing the guard stiffness, or limiting the guard's displacement, will improve protection to the occupants of the colliding vehicle and reduce the risk of passenger compartment intrusion.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.243

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0060.002
Scholarly communication0.0060.003
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0520.005

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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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 designNot applicable
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

Citations13
Published2000
Admission routes3
Has abstractyes

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