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Record W2563747725 · doi:10.7290/v72r3pmx

Experiences with Teaching Nuclear Security Professional Development Courses for Health Physicists

2016· article· en· W2563747725 on OpenAlexaff
Edward Waller, Jason T. Harris, Craig M. Marianno

Bibliographic record

VenueInternational Journal of Nuclear Security · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicNuclear Issues and Defense
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsProfessional developmentEngineering ethicsMathematics educationMedical educationComputer scienceEngineeringPsychologyMedicine

Abstract

fetched live from OpenAlex

Health physicists are professionals that are experts in the recognition, evaluation, and control of health hazards to permit the safe use and application of radiation. They typically have broad knowledge in radiation (ionizing and non-ionizing), biology, ecology and safety. With this wealth expertise we believe the health physicists would be useful partners in an effective security culture. As such over three years, a total of seven professional enrichment courses have been offered by the authors to health physics and radiation protection professionals, both nationally and internationally. Five have been through the Health Physics Society meetings, one through the International Radiation Protection Association meeting, and one at the Massachusetts Institute of Technology. This paper will briefly introduce these courses and will include learning objectives and descriptions of courses’ content. There was limited documented course participant feedback with only 1 of the 7 courses having documented course evaluations. Through both written and verbal feedback to the instructors it was clear the courses were well received.

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)0.001
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: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.362
Teacher spread0.344 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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