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Record W7094658721

VCB4523

2014· other· en· W7094658721 on OpenAlexaboutno aff

Bibliographic record

VenueCovenant University Repository (Covenant University) · 2014
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsRadionuclideRadiological weaponEffective dose (radiation)Gamma ray spectrometerAbsorbed dose rateAbsorbed doseHydrology (agriculture)Radium
DOInot available

Abstract

fetched live from OpenAlex

This study assessed the radioactivity level of Iju River sediments and its associated radiological risks exposure to human. Gamma absorbed dose rates were measured using a portable gamma spectrometer at an interval of 50 m between each point (Model No:RS-125 manufactured by Canadian Geophysical Institute). The measured absorbed gamma dose rates range from 22 to 59 nGy/h with the highest value noted in site 13. The mean activity concentrations of U-238, Th-232 and K-40 from Iju river sediments were 24.1 ± 0.4 Bq/kg, 35.2 ± 1.1 Bq/kg and 501.0 ± 11.1 Bq/kg, which were lower than the world average values of 32 and 45 for U-238 and Th-232 by 25% and 21% and higher than 412 Bq/kg for K-40 by a factor of 0.22 (22%).•This highest value of K-40 found in site 6 may be due to the presence of feldspartic minerals buried in the sediments.•Consequently, the radiological hazard indices were below the permissible limits except the mean value of 28 × 10-2 for excess lifetime cancer risk (ELCR) for the samples collected in site 6, which is higher than the average world value of 0.29 × 10- 3 by a factor of 0.03.•The regression model indicates that Th-232 attributes more radioactivity impacts on the soil sediments than the contributions of U-232 and K-40, as such, presumed to be the radionuclide parameter controlling the depositional process in the region.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.193
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0020.001
Scholarly communication0.0070.002
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.8070.745

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 head0.007
GPT teacher head0.162
Teacher spread0.155 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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