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Record W97117824 · doi:10.4271/2002-22-0018

ES-2 Dummy Biomechanical Responses

2002· article· en· W97117824 on OpenAlexaffabout
Katie Byrnes, Joseph Abramczyk, J. Berliner, Annette Irwin, Jack Jensen, Murthy Kowsika, Harold J. Mertz, Stephen W. Rouhana, Risa Scherer, Yibing Shi, Aleta Sutterfield, Lan Xu, Suzanne Tylko, Dainius Dalmotas

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2002
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsTransport Canada
Fundersnot available
KeywordsStandardizationComputer scienceEngineeringSimulationReliability engineering

Abstract

fetched live from OpenAlex

This technical paper presents the results of biomechanical testing conducted on the ES-2 dummy by the Occupant Safety Research Partnership and Transport Canada. The ES-2 is a production dummy, based on the EuroSID-1 dummy, that was modified to further improve testing capabilities as recommended by users of the EuroSID-1 dummy. Biomechanical response data were obtained by completing a series of drop, pendulum, and sled tests that are outlined in the International Organization of Standardization Technical Report 9790 that describes biofidelity requirements for the midsize adult male side impact dummy. A few of the biofidelity tests were conducted on both sides of the dummy to evaluate the symmetry of its responses. Full vehicle crash tests were conducted to verify if the changes in the EuroSID-1, resulting in the ES-2 design, did improve the dummy's testing capability. In addition to the biofidelity testing, the ES-2 dummy repeatability, reproducibility and durability are discussed. Finally, this technical paper will compare the biofidelity ratings of the current adult side impact dummies with the ES-2 dummy, which received an overall dummy biofidelity rating of 4.6.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.029
GPT teacher head0.280
Teacher spread0.251 · 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; both teacher heads agree on what is shown here.

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

Citations17
Published2002
Admission routes2
Has abstractyes

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