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Record W3195593850 · doi:10.1139/cjce-2020-0573

Evolution of bridge live load models and truck weight limits: the case of Manitoba, Canada

2021· article· en· W3195593850 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicTransport Systems and Technology
Canadian institutionsRTDS Technologies (Canada)University of ManitobaResearch Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTruckBridge (graph theory)TimelineTransport engineeringEngineeringDesign loadRange (aeronautics)Structural loadCivil engineeringAutomotive engineeringGeography

Abstract

fetched live from OpenAlex

Changes in the size and weight regulations for trucks have been used to improve their productivity, safety, and operational performance in Canada. In response to these changes, bridge design codes undergo modifications to envelop the potential range of trucks in operation. A five-decade timeline is presented to: (i) document how bridge codes and their live load models have evolved, with a focus on the Manitoba-specific HSS-25 truck; and (ii) discuss how responsive the bridge design codes have historically been to changes in truck size and weight regulations. While at times bridge codes are released in conjunction with expected regulation changes, there is often delay in the issuance of those codes. Assessments of the current truck fleet, which now includes long combination vehicles (LCVs), may be a consideration for future bridge live load models.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.500

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 head0.008
GPT teacher head0.151
Teacher spread0.143 · 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