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Record W6998833390

Birch Bay - The Story of the Region's Largest Beach Nourishment/Restoration Project

2022· article· en· W6998833390 on OpenAlexaboutno aff

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsBayShoreBeach nourishmentYardCoastal erosionStormwaterMainlandWork (physics)Port (circuit theory)
DOInot available

Abstract

fetched live from OpenAlex

Birch Bay is a large bay near the mainland Canadian border with extensive development and a previously degraded beach system. Development over the beach, gravel mining by the Air Force during the Cold War, subsequent groins and shore armor, and a system wide reduction in sediment supply had resulted in increased storm damage to Birch Bay Drive and the built environment, and loss of nearshore habitats. An initial beach nourishment concept was developed for the more developed portions of the bay by Wolf Bauer in 1975. A pilot beach nourishment project was built in 1986 which was monitored and renourished and proved to be successful. Decades of planning and project development work led to the 2014 to 2021 design, right of way acquisition, permitting, and construction. The recently completed 1.6-mile-long beach nourishment project (105,000 cubic yards of gravel and sand imported) includes a wide pedestrian trail, stormwater infiltration, backshore vegetation, and amenities such as crosswalks, benches, and refurbished parking. The $15.3 million project occurred through years of engagement between Whatcom County Public Works and community organizations. Steps included community meetings, feasibility studies, coordination with the Lummi and Nooksack Tribes and agencies, and pursuing grants. These efforts resulted in substantial transportation related funding, permit acquisition, on- and off-site mitigation, and required post project monitoring. The presentation will summarize the design and critical steps along the way and will include several pre-recorded video clips providing different perspectives on the value and history of the project.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.292
Threshold uncertainty score0.580

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0110.001
Scholarly communication0.0060.001
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0160.002

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 head0.018
GPT teacher head0.195
Teacher spread0.177 · 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 designObservational
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
Published2022
Admission routes1
Has abstractyes

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