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Record W2916700422 · doi:10.1115/1.4042906

Technical Communication During Nuclear and Radiological Emergencies With the Tools to Support International Assessment and Prognosis

2019· article· en· W2916700422 on OpenAlexaff
Margarita Tzivaki, Edward Waller

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2019
Typearticle
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsOntario Tech University
FundersInternational Atomic Energy AgencyU.S. Environmental Protection Agency
KeywordsRadiological weaponSuiteAgency (philosophy)Computer scienceSystems engineeringEngineering managementEngineeringMedicine

Abstract

fetched live from OpenAlex

The International Atomic Energy Agency's (IAEA) Incident and Emergency Centre (IEC) has custom designed software tools to support assessment and prognosis of nuclear and radiological emergency scenarios, aimed at ensuring consistent and concise technical reports for emergency assessments. In this paper the functionality, updating and structural development of emergency communications tools is presented, that lead the user through a series of questions with the aid of instructions that will collect relevant technical details and organize them into standardized reports. These reports can be exported for use in internal communication or communication with external stakeholders. This paper discusses enhancements in the suite of tools, specifically the reactor assessment tool (RAT), which was updated, the emergency response action, and the radiological source assessment tools, which were expanded and finally the development of two dose assessment tools (DAT) for internal and external exposure to radioactive substances.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.900
Threshold uncertainty score0.192

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.245
Teacher spread0.235 · 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 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
Published2019
Admission routes1
Has abstractyes

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