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Record W2907664875 · doi:10.2298/ntrp1803293a

Measurement of indoor radon concentrations in different dwellings in Arar, Saudi Arabia

2018· article· en· W2907664875 on OpenAlexaff
S. El‐Gamal

Bibliographic record

VenueNuclear Technology and Radiation Protection · 2018
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsScience North
Fundersnot available
KeywordsGeometric meanRadonMean valueMedicineStandard deviationGeometric standard deviationEffective dose (radiation)Environmental sciencePopulationNuclear medicineToxicologyMathematicsStatisticsEnvironmental health

Abstract

fetched live from OpenAlex

Indoor radon concentrations in 33 dwellings in Arar city were measured using a CR-39 detector. This work is the first in the region and was done to assess the health risks. The exposure time was about 4 months, from May to September 2017. It was found that the indoor radon concentration changed in the range from 7.7 to 89.1 Bqm-3 with an overall average of 44.05 ? 6.21 Bqm-3 while the geometric mean is 39.51 Bqm-3 with a geometric standard deviation of 1.67. These values are within the acceptable level set by the International Committee for Radiation Protection. The annual effective dose received by the population of Arar was reported and it varied in the range 0.16 -1.82 mSv with an average value of 0.9 ? 0.16 mSv and the geometric mean is 0.81 mSv. The exposure to radon progeny was studied where the minimum, maximum, average, and geometric mean of exposure are 0.83?10-3, 9.63?10-3, 4.76 ? 0.67? 10-3 and 5.05?10-3 WLM, respectively. Finally, for the estimation of cancer risks, the excess lifetime cancer risk was investigated. Its average value was 3.7?10-3 which is relatively higher.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.313
Teacher spread0.270 · 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 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

Citations2
Published2018
Admission routes1
Has abstractyes

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