MétaCan
Menu
Back to cohort
Record W334754504 · doi:10.21236/ada610277

Installation Development Environmental Assessment at Joint Base Andrews-Naval Air Facility Washington Prince George's County, Maryland

2013· report· en· W334754504 on OpenAlexaboutno aff
Michelle Cannella, Greg Hippert, Jennifer Jarvis, Tim Lavallee, Martha Martin, Samuel Pett, David Postlewaite, William Sharkey, Jeff Strong

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeorge (robot)Joint (building)Base (topology)EngineeringArchaeologyAeronauticsEnvironmental scienceGeographyCivil engineeringArtArt historyMathematics

Abstract

fetched live from OpenAlex

Abstract : JBA proposes a program of targeted construction and demolition activities intended to improve its operational efficiency and ensure that the installation can sustain its current and future national security operations and mission-readiness status. The proposed activities are: * Construct a Helicopter Operations Facility. * Construct a new fitness center and demolish the West Fitness Center (Building 1444). * Construct a new Child Development Center (CDC) and demolish CDC #1 (Building 4575). * Construct a Security Forces Group complex and demolish two buildings (Building 1642 [Base Library] and Building 1605 [a vehicle wash rack]) that are on the site selected for the complex. * Enlarge the parking lot adjacent to Building 1845. * Demolish Building 1988 (a traffic check house) and construct a new traffic check house in the same location. * Demolish Buildings 1429 (a generator building), 1679 (Chapel 3), and 1732 (a heat plant), and the canopy and fuel tanks at Building 1685 (a former Army and Air Force Exchange Service gas station). * Modify three entry control facilities (Main Gate, Pearl Harbor Gate, and Virginia Gate).

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.433

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.002

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 head0.021
GPT teacher head0.224
Teacher spread0.203 · 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
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicNuclear and radioactivity studiesFrench-language works237,207