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Record W243307247 · doi:10.21236/ada612757

Environmental Assessment for Replacement of Taxiway Sierra, Taxiway Whiskey, Pad 12, and Pad 13 at Joint Base Andrews-Naval Air Facility Washington, Prince George's County, Maryland

2013· report· en· W243307247 on OpenAlexaboutno aff
Michelle Cannella, Jennifer Jarvis, Tim Lavallee, Samuel Pett, David Postlewaite, William Sharkey, Jeff Strong

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsGeorge (robot)EngineeringHistory

Abstract

fetched live from OpenAlex

Abstract : JBA proposes to improve its operational efficiency by replacing Taxiways Sierra and Whiskey and Pads 12 and 13 on the airfield. The task for Taxiway Sierra would include demolishing and replacing approximately 49,500 square yards (10 acres) of existing pavements and shoulders and improving or replacing the taxiway's drainage, signage, and lighting systems. The task for Taxiway Whiskey would include replacing approximately 208,100 square yards (43 acres) of existing pavements and shoulders and improving or replacing the taxiway's drainage, signage, and lighting systems. Taxiway Sierra would be replaced before work on Taxiway Whiskey began. The area of Pad 12 is approximately 7,340 square yards (1.5 acres), and the area of Pad 13 is approximately 7,280 square yards (1.5 acres). The pavement on both pads is about 10 inches thick. Replacing the pads would include excavation, site preparation, striping, restoration of disturbed areas, and all necessary and essential utilities work to satisfy JBA operational requirements. Pads 12 and 13 would be replaced after work on Taxiway Whiskey was completed. This environmental assessment (EA) has been prepared to address the potential impacts of undertaking the abovementioned project. This EA has been prepared to report an evaluation of the proposed action and alternatives, including the No Action Alternative. Resource areas addressed in the EA are noise, air quality, safety and occupational health, earth resources, water resources, infrastructure/utilities, transportation, hazardous materials and wastes, biological resources, cultural resources, historic and archaeological resources, socioeconomics (including environmental justice and protection of children), land use and visual resources, and sustainability and greening. The Draft EA was made available to agencies and the public for a 30-day comment period from March 7, 2013, to April 7, 2013.

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)0.000
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: none
Teacher disagreement score0.123
Threshold uncertainty score0.244

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.023
GPT teacher head0.271
Teacher spread0.248 · 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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