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Record W4250845035 · doi:10.1063/1.4797297

Safer vehicles by redesign

2006· article· en· W4250845035 on OpenAlexaboutno aff
Marc Ross, Deena Patel, Tom Wenzel

Bibliographic record

VenuePhysics Today · 2006
Typearticle
Languageen
FieldEngineering
TopicTransportation Safety and Impact Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTruckSAFERVehicle safetyAeronauticsTransport engineeringEngineeringComputer scienceComputer securityAutomotive engineering

Abstract

fetched live from OpenAlex

Ross, Patel, and Wenzel reply: These two thoughtful letters illustrate the importance of myriad details of vehicle design to dangers and safety in traffic. The height of the lights of most SUVs and trucks, which temporarily blind car drivers at night, is a significant risk (which has been crudely quantified in fatality statistics as around 100 per year). Ian Halliday’s comments about daytime running lights are indirectly supported by the impressive fatality reductions that are being achieved in Canada (see figure 2 of our article). Those reductions should inspire Americans to question the less-than-impressive claims of success made for US traffic safety programs. Vehicle design is critical to traffic safety. Specific design features, such as the heights of car seats versus the heights of “truck” fronts, where the trucks are merely serving as car substitutes, are among the most important issues for safety design. Differences in vehicle structures are important; but as we argued in our article, the laws of physics do not imply that vehicle mass, as such, is a safety feature. Observation suggests it is relatively unimportant in today’s fleet.© 2006 American Institute of Physics.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.629
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.190
Teacher spread0.184 · 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 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

Citations0
Published2006
Admission routes1
Has abstractyes

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