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Record W2117565823 · doi:10.1061/9780784413067.013

Endangered Species Act and Marine Mammal Protection Act Permitting in the Pacific Northwest

2013· article· en· W2117565823 on OpenAlexfundno aff
Tabitha Reeder, Brian Carrico, Dan Gunderson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMarine and Offshore Engineering Studies
Canadian institutionsnot available
FundersU.S. Army Corps of EngineersU.S. Fish and Wildlife ServiceUniversity of Waterloo
KeywordsWork (physics)ScheduleEndangered speciesDocumentationPort (circuit theory)Environmental resource managementEnvironmental protectionEnvironmental planningEnvironmental scienceBusinessEngineeringComputer scienceEcologyHabitat

Abstract

fetched live from OpenAlex

The construction, maintenance, and repair of critical port infrastructure in the marine and freshwater environments of the Pacific Northwest frequently requires in-water and/or overwater work, which triggers specific requirements for federal environmental permitting and documentation. The Endangered Species Act (ESA) and the Marine Mammal Protection Act (MMPA) are the two federal regulations that generally have the greatest potential effect on project design, cost, and schedule. This paper discusses the current regulatory climate surrounding ESA and MMPA compliance by comparing the impacts of these regulations on two recently permitted projects. The projects are located at sites within the Puget Sound and on the Lower Columbia River, and range from routine activities, such as pile repair and replacement, to the construction of new marine terminals. The paper presents the design requirements for the projects, the way in which the project addressed ESA and MMPA compliance, and how the compliance process affected the project design, cost, and/or schedule. The comparative analysis concludes with a summary of the potential effects to project schedule, design, and cost, and a discussion of the ways in which project managers, design teams, engineers, and environmental staff can work to minimize these potential issues.

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)0.003
metaresearch head score (Gemma)0.005
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: Other · Consensus signal: Other
Teacher disagreement score0.617
Threshold uncertainty score0.771

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.009
GPT teacher head0.177
Teacher spread0.168 · 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
GenreOther

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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