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Record W2161913503 · doi:10.1061/9780784413067.098

Coastal Engineering Analysis for Airport Improvements, False Pass, AK

2013· article· en· W2161913503 on OpenAlexaff
Eduardo Sierra-Carrascal, Kenneth J. Connell, Greg Curtiss, Philip D. Osborne

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsRunwayCurrent (fluid)ShoreMarine engineeringStormAcoustic Doppler current profilerEnvironmental scienceRange (aeronautics)Flow (mathematics)MeteorologyGeologyEngineeringOceanographyGeographyAerospace engineering

Abstract

fetched live from OpenAlex

A coastal engineering and numerical model (Delft3D) assessment of waves and flow was performed to support the Alaska Department of Transportation and Public Facilities (ADOT&PF) proposed extension of the False Pass Airport runway into Isanotski Strait on the eastern shore of Unimak Island. The objective of this analysis was to provide design current, water level, and preliminary wave parameters for the project site, and to assess potential project impact on tidal circulation and the wave field resulting from the proposed airport runway extension design. This study was executed by analyzing existing data, collecting new water level and acoustic Doppler current profiler (ADCP) data used to successfully validate the numerical model, and simulating 50-year design waves coupled with flow in the vicinity of the Isanotski Strait. Significant wave height simulated with a 50-year design storm range between 0.3 - 1.1 m in the immediate vicinity of the design project extension. Moderate changes in current velocity and circulation are noted near the east side of the runway extension with current speed differences up to ±0.5 m/s.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0250.005

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 head0.006
GPT teacher head0.176
Teacher spread0.169 · 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
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
Published2013
Admission routes1
Has abstractyes

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