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Record W4410281716 · doi:10.18280/ijsse.150318

Evaluation of the Impact of Indoor and Outdoor Background Ionizing Radiation on Health risk in two Physics University Laboratories

2025· article· en· W4410281716 on OpenAlexvenueno aff
M.E.M. Eisa, Mohamed A. Ali, Mustafa Abualreish, S. E. I. Yagoub, Lamiaa Galal Amin

Bibliographic record

VenueInternational Journal of Safety and Security Engineering · 2025
Typearticle
Languageen
FieldChemical Engineering
TopicChemical Safety and Risk Management
Canadian institutionsnot available
FundersNorthern Border University
KeywordsIonizing radiationBackground radiationEnvironmental sciencePhysicsAeronauticsEngineering physicsEngineeringMedical physicsRadiationNuclear physicsIrradiation

Abstract

fetched live from OpenAlex

This study investigates the levels and health implications of indoor and outdoor background gamma radiation in two university physics laboratories in Sudan University of Scienece and Technology, Sudan.Given the constant exposure to ionizing radiation from natural and artificial sources, including building materials and radioactive teaching aids, the study aimed to quantify radiation exposure risks to staff, students, and visitors.Using a Geiger-Mller (GM) tube and digital counter, radiation levels were measured at various points in and around the laboratories.Results showed that average indoor radiation doses were consistently higher than outdoor levels in both laboratories, with Lab 1 recording an average indoor dose of 150.92 nSv/h compared to 114.73 nSv/h outdoors, and Lab 2 showing 81.91 nSv/h indoors versus 71.42 nSv/h outdoors which is less than the global radiation threshold.Although some indoor readings approached established high-dose thresholds, none significantly exceeded them.The data suggest that indoor sources, possibly building materials or equipment, contribute to elevated exposure, though not at levels requiring immediate intervention.These findings support the need for continued monitoring and the establishment of safety guidelines to mitigate long-term exposure risks in educational laboratory environments.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score0.234

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 studies0.0000.000
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 head0.290
Teacher spread0.280 · 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 designSimulation or modeling
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
Published2025
Admission routes1
Has abstractyes

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