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Record W2301772378 · doi:10.2172/1088052

Report on Project Action Sheet PP05 task 3 between the U.S. Department of Energy and the Republic of Korea Ministry of Education, Science, and Technology (MEST)

2013· report· en· W2301772378 on OpenAlexaboutno aff
Mark K. Snell

Bibliographic record

Venuenot available
Typereport
Languageen
FieldComputer Science
TopicInformation and Cyber Security
Canadian institutionsnot available
FundersNational Nuclear Security AdministrationSandia National LaboratoriesU.S. Department of Energy
KeywordsChristian ministryTask (project management)Action (physics)Computer scienceOperations researchProcess (computing)Control (management)EngineeringEngineering managementSimulationPolitical scienceLawArtificial intelligenceSystems engineeringOperating system

Abstract

fetched live from OpenAlex

This report documents the results of Task 3 of Project Action Sheet PP05 between the United States Department of Energy (DOE) and the Republic of Korea (ROK) Ministry of Education, Science, and Technology (MEST) for Support with Review of an ROK Risk Evaluation Process. This task was to have Sandia National Laboratories collaborate with the Korea Institute of Nuclear Nonproliferation and Control (KINAC) on several activities concerning how to determine the Probability of Neutralization, P<sub>N</sub>, and the Probability of System Effectiveness, P<sub>E</sub>, to include: providing descriptions on how combat simulations are used to determine P<sub>N</sub> and P<sub>E</sub>; comparisons of the strengths and weaknesses of two neutralization models (the Neutralization.xls spreadsheet model versus the Brief Adversary Threat-Loss Estimator (BATLE) software); and demonstrating how computer simulations can be used to determine P<sub>N</sub>. Note that the computer simulation used for the demonstration was the Scenario Toolkit And Generation Environment (STAGE) simulation, which is a stand-alone synthetic tactical simulation sold by Presagis Canada Incorporated. The demonstration is provided in a separate Audio Video Interleave (.AVI) file.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.780
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

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

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 head0.021
GPT teacher head0.292
Teacher spread0.271 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations5
Published2013
Admission routes1
Has abstractyes

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