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Record W2729258378 · doi:10.1061/9780784480809.038

The Remediation of Buckeye Lake Dam, Ohio: Deep Mixing as an Interim Risk Reduction Measure and Key Component of Final Design

2017· article· en· W2729258378 on OpenAlexaff
Daniel P. Stare, George M. Filz, Donald A. Bruce

Bibliographic record

VenueGrouting 2017 · 2017
Typearticle
Languageen
FieldEngineering
TopicDam Engineering and Safety
Canadian institutionsMRF Geosystems (Canada)
Fundersnot available
KeywordsInterimLeveeCivil engineeringAbutmentEngineeringEnvironmental remediationWork (physics)Environmental scienceHydrology (agriculture)Geotechnical engineeringArchaeologyGeography

Abstract

fetched live from OpenAlex

Rehabilitation of Buckeye Lake Dam in central Ohio presented significant logistical and technical challenges given the history of the site, limited access and the proximity of private residences to the work. Covering almost 200 years, Buckeye Lake has a rich and varied history of industry and recreation. Presently a State Park administered under the Ohio Department of Natural Resources, the seepage, stability and hydraulic performance of the existing embankment dam was deemed unacceptable necessitating rehabilitation of the structure. Flanked by private residential and commercial properties at the downstream dam crest, construction of the new seepage barrier and new dam necessitated selection of appropriate construction methods and close coordination with the public. After presenting a brief history of the site, this paper focuses primarily on the different deep soil mixing methods utilized to construct the seepage barrier as well as the use of additional deep soil mixing downstream of the seepage barrier to construct a composite gravity dam structure.

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)0.001
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 score0.339
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.035
GPT teacher head0.249
Teacher spread0.214 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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