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Record W4221120846 · doi:10.1061/9780784484029.044

Performance of Station Excavations for LA Metro K (Crenshaw/LAX) Line

2022· article· en· W4221120846 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.

Bibliographic record

VenueGeo-Congress 2022 · 2022
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsExcavationGeotechnical engineeringSettlement (finance)Deflection (physics)AlluviumStiffnessMetro stationGeologyEngineeringStructural engineeringComputer scienceGeomorphology

Abstract

fetched live from OpenAlex

This paper presents the effects of excavations in Los Angeles on the surrounding ground surface. Three large excavations with varied support systems for stations constructed as part of the K (Crenshaw/LAX) Line Transit Project provide an opportunity to acquire data through an extensive geotechnical investigation and field monitoring program to further our understanding of soil-structure interaction and excavation-induced ground deformations. The ground conditions encountered on site include alluvial deposits of silts, clays, and sands. The data acquired illustrates that ground displacement and wall deflection largely depend on the stiffness of the excavation support system. Support systems with relatively high stiffness are able to successfully limit surface settlement behind excavations. The data shows that heaving caused by unloading governs the soil response given the relatively small lateral support wall deformations. Current empirical models are unable to capture this ground behavior. An update of these empirical relations is needed to represent this behavior in support of the design of future excavations.

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 score0.034
Threshold uncertainty score0.448

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 head0.213
Teacher spread0.205 · 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