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Record W4404386818 · doi:10.1093/rpd/ncae129

Development of evaluation method for radiocesium availability in soil by biomimetic approach

2024· article· en· W4404386818 on OpenAlexaff
Akira Takeda, Yusuke Unno, Mathew J.B. Swallow, Yasumi Yagasaki, Tetsuo Yasutaka, Naofumi Akata

Bibliographic record

VenueRadiation Protection Dosimetry · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsMount Royal University
Fundersnot available
KeywordsTRACEREnvironmental scienceEnvironmental chemistrySoil scienceDiffusionConcentration gradientChemistry

Abstract

fetched live from OpenAlex

Applicability of biomimetic approach with simulation of plant uptake for assessment of radiocesium availability in soil was investigated. The soil spiked with 137Cs tracer was contacted with wicking material and copper-substituted prussian blue (Cu-PB), which simulate transpirationally induced mass flow and concentration gradient-induced diffusion of radiocesiumin the soil, respectively. Comparison of the removed 137Cs to the wick and the wick + Cu-PB from the soil during the contact period of 12 weeks suggested that the diffusion process has larger contribution than the mass flow process in radiocesium dynamics in root zone. The change of the removed rate of 137Cs from the soil was reflected that its availability decreased with the time elapsing and with subjecting repeated wet-dry treatment. The results suggest that the biomimetic approach can be applicable to the realistic evaluation of the availability of radiocesium in soil.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.000
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 head0.018
GPT teacher head0.287
Teacher spread0.269 · 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 designBench or experimental
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
Published2024
Admission routes1
Has abstractyes

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