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Record W2137794813 · doi:10.1061/41016(314)15

Sioux Narrows Bridge — Context Sensitive Replacement of a Heritage Timber Truss Bridge

2008· article· en· W2137794813 on OpenAlexaffabout
R Radolli, Raymond Krisciunas

Bibliographic record

VenueStructures Congress 2008 · 2008
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsProcter & Gamble (Canada)Ministry of Transportation of Ontario
Fundersnot available
KeywordsBridge (graph theory)Context (archaeology)TrussChristian ministryTruss bridgeEngineeringNational heritageCivil engineeringSpan (engineering)Architectural engineeringArchaeologyGeographyComputer sciencePolitical scienceLibrary scienceLaw

Abstract

fetched live from OpenAlex

The Sioux Narrows Bridge in Northern Ontario was a 64m long timber truss structure originally constructed in the 1930's. It was located across a narrows on Lake of the Woods in the picturesque, historic community of Sioux Narrows in Northern Ontario and is owned by the Province of Ontario, Ministry of Transportation (MTO). It had been heralded as one of the longest single span timber bridges in the world. In light of its age and uniqueness the Province of Ontario listed the structure on the Ontario Heritage Bridge List [MofC 1983]. In 2002 the bridge was discovered to be in a state of progressive collapse and a decision was ultimately made to replace it. From a planning and engineering perspective the heritage designation required the project team to consider heritage and aesthetic issues as an integral component when examining alternatives to address the structural deficiencies. The final solution was one where the original heritage features of the bridge were preserved while at the same time providing a new, durable and highly functional bridge.

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.893
Threshold uncertainty score0.212

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.228
Teacher spread0.212 · 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

Citations0
Published2008
Admission routes2
Has abstractyes

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