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Record W2073866063 · doi:10.1080/13588265.2013.815019

Human rib response to different restraint systems in frontal impacts: a study using a human body model

2013· article· en· W2073866063 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Crashworthiness · 2013
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsnot available
FundersUniversité de SherbrookeEuropean CommissionUniversity of Virginia
KeywordsHuman-body modelHuman bodyPoison controlHuman factors and ergonomicsInjury preventionPhysical medicine and rehabilitationEngineeringPsychologyComputer scienceMedicineMedical emergencyAnatomyArtificial intelligence

Abstract

fetched live from OpenAlex

Finite-element human body models (FE-HBMs) can be used to evaluate restraint systems by predicting thoracic injury. The biofidelity assessment of an FE-HBM Total HUman Model for Safety (THUMS) 50th percentile male occupant and the characterisation of its rib response to loads from frontal car crashes are the objectives of this study. The rib-cage mesh of THUMS version 3.0 was refined to improve the shoulder-belt interaction, material properties of lungs and skin modified, and the model biofidelity assessed against tests representative of frontal crashes. The modified THUMS response improved with respect to the baseline model. The modified THUMS was used to analyse the rib loading in frontal impacts. The rib response included shear, torsion and bending in belt and airbag-like load cases. This indicates that a criterion based only on rib anteroposterior compression may not be enough to predict fractures and that a criterion should consider compression, torsion and shear.

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.

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)0.000
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 score0.853
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.039
GPT teacher head0.368
Teacher spread0.329 · 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