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Record W2086413710 · doi:10.5539/apr.v4n3p70

Equivalent Radiation Doses in Area of North Jordan

2012· article· en· W2086413710 on OpenAlexvenueno aff
Nabil Najib Alzubaidy

Bibliographic record

VenueApplied Physics Research · 2012
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsRadonDosimeterNuclear trackEnvironmental scienceCR-39Radiation doseAbsorption (acoustics)Equivalent doseRadiationRadiation monitoringNuclear medicineMaterials scienceIrradiationRadiochemistryDetectorDosimetryMedicinePhysicsChemistryOpticsNuclear physicsComposite material

Abstract

fetched live from OpenAlex

In this research the authors measured radon gas concentration inside Hakama homes and calculated equivalent radiation doses in the study area. The study started from 1 June 2011 to 1 September 2011. Study area was divided into four sectors (H East, H West, H North and H South). About 200 dosimeters containing highly pure CR-39 were distributed randomly among the houses of the different sectors. Two dosimeters were distributed in each house (first in the living room and the second in the guest room). The indoor dosimeters were collected after three months. The collected detectors were chemically etched using 30 % KOH for 8 hours at 70 °C. An optical microscope was used to measure the nuclear alpha track density on the detectors surfaces. The author found that the average radon concentration in the study area was ranged from 30.2 Bq/m3 in the sector H East to 25.7 Bq/m3 in the sector H South. Moreover; the average radon concentration in the living rooms in the study area was 18.8 Bq/m3 which is below that in the guest rooms 37 Bq/m3. Radon contributes in increasing of absorption radiation dose. The calculated equivalent radiation dose in the study area was 0.68. The average radon concentration in the study area was below the Jordanian national level.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.389

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.389
GPT teacher head0.514
Teacher spread0.125 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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