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Record W2920968664

Assessment of Millennium Pipeline Project, Lake Erie crossing : ice scour, sediment sampling, and turbidity modeling

2000· report· en· W2920968664 on OpenAlexfundno aff
J. H. Lever

Bibliographic record

VenueUS Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core) · 2000
Typereport
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
FundersCold Regions Research and Engineering LaboratoryEngineer Research and Development CenterU.S. Army Corps of EngineersMemorial University of NewfoundlandU.S. Department of Defense
KeywordsSampling (signal processing)Environmental scienceSedimentHydrology (agriculture)TurbidityOceanographyPipeline (software)GeologyEngineeringGeomorphologyGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

ERDC researchers assessed the Millennium Pipeline Project on three topics related to its proposed crossing of Lake Erie: 1) the potential for pipeline damage by ice scour, 2) adequacy of the sampling program to identify contaminated sediments, and 3) adequacy of the modeling for turbidity and sediment deposition resulting from pipeline-trench excavation. Inclusion of additional scour data and reanalysis resulted in a 25% increase in the estimated 100-year scour depth near the U.S. shore and a consequent increase in the design trench depth by about 20%. Question-answer exchanges resolved ERDC concerns regarding sediment sampling and turbidity/deposition modeling.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.107
GPT teacher head0.364
Teacher spread0.256 · 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.

Study designNot applicable
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
Published2000
Admission routes1
Has abstractyes

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