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Record W1573055292 · doi:10.21236/ada630613

Environmental Assessment for the Construction of Power and Fiber Optic Lines to Facilities in the Yukon Training Area, Alaska-Phase 3

2006· report· en· W1573055292 on OpenAlexaboutno aff
Sarah C. Conn Brent, James Nolke, Tom Slater, Bill Harvard, M. Bergey, Phil Martin, Forrest McDaniel, Roger Sayer

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsTraining (meteorology)Phase (matter)Remote sensingEnvironmental scienceGeographyMeteorologyPhysics

Abstract

fetched live from OpenAlex

Abstract : The 354th Fighter Wing (FW) operates, maintains, and trains combat forces in close air support and interdiction missions in support of the war plans in three operational theaters. The 354 FW s mission is to train and equip personnel for close air support of ground troops in an arctic environment. The range combat training facilities operated by Eielson Air Force Base (Eielson) are some of the finest in the world. Each year the 353rd Combat Training Squadron, based at Eielson, conducts four joint training exercises with Elmendorf Air Force Base, as well as other US Air Force (USAF) units and units from allied countries. The Air Combat Maneuvering Instrumentation (ACMI) system was installed on US Army range lands that comprise Eielson s range facilities. The continued efficient and reliable operation of this range facility and training program is of vital importance to Eielson s mission. The proposed action will result in the construction of approximately 25.7 miles of electrical transmission and fiber optic communication lines in various locations within Fort Wainwright s Yukon Training Area (YTA), Alaska. The fiber optic cable would be collocated on the power line poles, with the point of origin at the Cope Thunder range operations facility on Flightline Avenue. This power and communications system will significantly enhance the operational efficiency and reliability of the range, as well as cut operational costs by replacing expensive constant run diesel generators and propane gas fired power systems.

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)0.000
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 score0.107
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.278
Teacher spread0.256 · 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
Published2006
Admission routes1
Has abstractyes

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