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Record W189879061

BRIDGES ON THE TRANS LABRADOR HIGHWAY

2003· article· en· W189879061 on OpenAlexaboutno aff
Gao Jin, P Lester, Thomas McCarthy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsCulvertBayTributaryTrussGeologyHydrology (agriculture)Civil engineeringEngineeringGeographyGeotechnical engineeringCartography
DOInot available

Abstract

fetched live from OpenAlex

In 1983, the Province of Newfoundland and Labrador began building the Trans Labrador Highway (TLH). Upgrading and new construction was undertaken in 3 phases starting in 1997. Phase II (Red Bay to Cartwright), a 325 km all-weather gravel highway passing through uninhabited and undeveloped wilderness country, is intersected by 150 watercourses, ranging from small streams to large rivers (Alexis and St. Lewis). These 2 large rivers created difficult challenges for the planning and design of the 110 m single span truss bridges, including site optimization, road travel minimization and maintenance through mountainous terrain, and/or traversing deep tidal inlets. Environmental considerations using survey data from 1823 hydrometric surveys (depth soundings) were used along with a hydrological/hydraulic study (tidal effects), as well as river and ocean ice concerns. Bridge structures over the Alexis and St. Lewis Rivers consisted of steel truss designs with steel grid deck and reinforced concrete abutments. Problems encountered included route layout and selection, geoscience considerations, hydrology, hydraulics, causeway construction, bridge launching, and environmental issues. Weak clayey silts had to sustain a load of up to a 30 m high causeway at the abutments. Part of Phase III is the forthcoming bridge over the Churchill River. Problems include the search for a good crossing point, hydraulic design and hydrological considerations, foundation concerns, ice forces, and erection methods. Completion of the TLH will foster new opportunities in tourism, forestry, and mining; provide improved accessibility; and reduce travel costs.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.706
Threshold uncertainty score0.584

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0410.008

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 head0.009
GPT teacher head0.174
Teacher spread0.165 · 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
Published2003
Admission routes1
Has abstractyes

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