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Record W575637696

Streamlining the Bridge Design Process

2006· article· en· W575637696 on OpenAlexvenueno aff
Kevin Willis

Bibliographic record

VenueBridges Conversations in Global Politics and Public Policy · 2006
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsBridge (graph theory)DeliverableComputer scienceProcess (computing)Software engineeringAutomationSoftwareEngineering design processQuality (philosophy)Engineering drawingSystems engineeringEngineeringProgramming language
DOInot available

Abstract

fetched live from OpenAlex

More than 50 bridge structures are included in a massive project to rebuild Milwaukee's Marquette Interchange. This article describes how the project's bridge design firm is using technology and innovation to save both time and money. To take advantage of the structured nature of bridge design and to automate portions of the detailed design phase, the design firm has developed a series of computer programs that allow the firm to deliver bridge design services with improved efficiency and better quality. A custom automation tool was developed that reads the output of the conventional design software. This tool then generates a text file in a standard format that contains information needed to create each drawing. The text fields simplify the programming task by providing only the parametric information that defines the design. A program was also created that reads the text fields and creates finished deliverable drawings based on the fields' contents. The program produces drawings automatically that reflect the design intent accurately, simplifying the quality assurance process. Design changes can also be accommodated easily.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.772
Threshold uncertainty score0.708

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 head0.017
GPT teacher head0.254
Teacher spread0.236 · 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 designTheoretical or conceptual
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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