MétaCan
Menu
Back to cohort
Record W4406420118 · doi:10.51501/jotnafe.v38i2.125

Forensic Engineering Analysis of a Crash Caused by Swingout of an Articulated Booster on a Semi-Trailer

2022· article· en· W4406420118 on OpenAlexaff
Donald Fournier, Steven H. Mitchell, Shawn Ray, Reza Vaghar

Bibliographic record

VenueJournal of the National Academy of Forensic Engineers · 2022
Typearticle
Languageen
FieldEngineering
TopicMarine and Coastal Research
Canadian institutionsDucks Unlimited Canada
Fundersnot available
KeywordsTrailerCrashBooster (rocketry)AeronauticsComputer scienceEngineeringAutomotive engineeringAerospace engineering

Abstract

fetched live from OpenAlex

An unloaded lowboy trailer with an articulated booster axle was traversing a curved exit ramp when the trailer tires lost traction, and the booster axle redirected the rear of the trailer into oncoming traffic. The reconstruction used a detailed analysis of roadway geometry, truck geometry, and suspension characteristics to determine the cause of the trailer swingout. A comprehensive topographical map was created from 3D laser scans. The interaction of each tire with the pavement surface was used to determine the individual wheel loads. Dynamic analysis of the curved path quantified the speed required to cause loss of traction and subsequent swingout.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.257
Teacher spread0.242 · 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 designSimulation or modeling
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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the National Academy of Forensic EngineersSame topicMarine and Coastal ResearchFrench-language works237,207