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Record W2006585413 · doi:10.1680/tran.2000.141.1.43

The North Hollywood Project, Los Angeles

2000· article· en· W2006585413 on OpenAlexaff
A R BIGGART, John G. Hawley, J. Townsend

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Transport · 2000
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsHatch (Canada)
FundersCalifornia Department of Transportation
KeywordsEngineeringShotcreteTrack (disk drive)RunwayRailway tunnelRailway lineCivil engineeringGeologyMining engineeringGeotechnical engineeringForensic engineeringMechanical engineering

Abstract

fetched live from OpenAlex

The North Hollywood Project is a 10 km twin tunnel extension to the Los Angeles Metro Red Line valued at US$1·3 billion. The extension includes three stations constructed by cut and cover methods, together with the rail track, the necessary support systems, and rolling stock. This paper covers the main civil engineering construction of the project. The construction of the cut and cover stations is described. A number of interesting features of the tunnel construction are described, including the boring of the main running tunnels using tunnel boring machines (TBMs), the construction of a special seismic section of oversize tunnel through a major fault using shotcrete lining, track level rooms, starter tunnels and cross passages between running tunnels. An important emphasis of the paper is on the rock tunnels driven by the TBMs. The difficulties caused by severe geological conditions include dealing with water at high pressure and fissure grouting to reduce water inflow through the permanent lining. Both the temporary and the permanent tunnel lining are described.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.178
Teacher spread0.173 · 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 designSimulation or modeling
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
Published2000
Admission routes1
Has abstractyes

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