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Record W582795887 · doi:10.17226/13954

Bridge Rating Practices and Policies for Overweight Vehicles

2006· book· en· W582795887 on OpenAlexaboutno aff

Bibliographic record

VenueTransportation Research Board eBooks · 2006
Typebook
Languageen
FieldEngineering
TopicInfrastructure Maintenance and Monitoring
Canadian institutionsnot available
Fundersnot available
KeywordsBridge (graph theory)Transport engineeringOverweightBusinessStructural engineeringEngineeringMedicineObesity

Abstract

fetched live from OpenAlex

This synthesis focuses on overweight vehicle bridge permit processes. Information on state and provincial bridge rating systems, bridge evaluation practices and permit policies as they relate to overweight and oversize vehicles is highlighted and discussed. This report is intended to assist in the understanding of the reasons for nonuniform permitting practices. The report reviews specifications, software types, treatment of nonstandard configurations, and allowance for in-place dead loads; processes of permit review; and personnel assigned to permit review. A survey was distributed to transportation agencies at the state level in the United States and to Canadian provinces. A literature search was undertaken to identify relevant research reports, papers, and other publications for review and summation. Additional information was acquired from telephone interviews with targeted individuals and organizations to supplement the survey and literature search.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.086
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.047
GPT teacher head0.333
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations7
Published2006
Admission routes1
Has abstractyes

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