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Record W4404448177 · doi:10.1016/j.jenvrad.2024.107566

Soil-to-plant transfer factors of uranium and thorium in mining and non-mining districts of Ghana

2024· article· en· W4404448177 on OpenAlexafffund
Edward Ankapong, Opoku Gyamfi, Victor Agyei, Matt Dodd, Osei Akoto, Godfred Darko

Bibliographic record

VenueJournal of Environmental Radioactivity · 2024
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsRoyal Roads University
FundersRoyal Roads University
KeywordsThoriumUraniumEnvironmental scienceTransfer factorRadionuclideUranium miningEffective dose (radiation)Soil testRadiation monitoringEnvironmental chemistrySoil waterSoil scienceChemistryNuclear medicineMaterials scienceBiologyPhysics

Abstract

fetched live from OpenAlex

The activity concentrations of natural radionuclides in water, soil, cassava, cocoyam and yam grown in two mining districts and a non-mining district in Ghana were determined using a high-resolution gamma spectroscopy system with high-purity germanium detector. The estimated absorbed dose for soil from Amansie, Konongo, and Mampong were 206 nGy/h, 224 nGy/h and 198 nGy/h, respectively, which were all above 60 nGy/h set by the United Nations Scientific Committee on the Effects of Atomic Radiation. The soil-to-plant transfer factors (TF) for 2 ³⁸U, 2 ³ 2 Th, and ⁴⁰K ranged from 0.11 to 1.11, 0.03 to 2.39, and 0.03 to 22.07, respectively. The results showed that the highest TF for 238 U and 232 Th were 1.11 and 2.39, respectively in cassava. There was no significant variation in the TF of 238 U and 232 Th among the soils in the different communities. The estimated transfer factors for 238 U and 232 Th for cassava, cocoyam and yam were higher than that reported by the International Atomic Energy Agency. • Natural radioactivities in the communities are higher than the world average. • Estimated absorbed dose is higher than the threshold 60 ngy/h. • Soil-to-cassava transfer factors for uranium and thorium found.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.036
GPT teacher head0.312
Teacher spread0.275 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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