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Record W578209612

CVSA AND MCSAP: A FEDERAL-STATE PARTNERSHIP

2004· article· en· W578209612 on OpenAlexaboutno aff
Stephen A Keppler

Bibliographic record

VenueJournal of transportation law, logistics, and policy · 2004
Typearticle
Languageen
FieldEngineering
TopicTransportation Safety and Impact Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsEnforcementCertificationGeneral partnershipBusinessMotor carrierLaw enforcementTransport engineeringCrashService (business)Computer securityEngineeringFinanceLawPolitical scienceComputer scienceMarketing
DOInot available

Abstract

fetched live from OpenAlex

The Commercial Vehicle Safety Alliance (CVSA), an association of state, provincial and federal officials is responsible for the administration and enforcement of motor carrier safety laws in the United States, Canada and Mexico. Its mission is accomplished through establishment of effective motor carrier, driver, vehicle and cargo safety standards along with compliance, education, training and enforcement activities. The Motor Carrier Safety Assistance Program (MCSAP), created to improve motor carrier safety and reduce commercial vehicle crashes, is another example of a federal aid program that has worked. As a result of the partnership between CVSA and MCSAP, the following has been accomplished: North American standard roadside inspection procedures; North American standard out-of-service criteria; out-of-service and other defect repair verification procedures; complaint control procedures; uniform maximum firm schedules; inspector and instructor training, certification and recertification practices and procedures; safety information, software and data systems; and performance of roadside inspections, traffic enforcement, compliance reviews and crash and incident investigations.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score0.522

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 head0.016
GPT teacher head0.259
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 designObservational
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
Published2004
Admission routes1
Has abstractyes

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