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Record W4396954385 · doi:10.1134/s1066362224020174

Statistical Evaluation of the Tritium Content of Aquatic Ecosystems at NPP Sites

2024· article· en· W4396954385 on OpenAlexaboutno aff
L. G. Bondarenko, V. N. Dushin, A. D. Sadykin, S. I. Shabalev

Bibliographic record

VenueRadiochemistry · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryTritiumAquatic ecosystemEnvironmental chemistryEcosystemRadiochemistryEcologyNuclear physics

Abstract

fetched live from OpenAlex

Abstract The lognormal statistical distribution was used to present the reliable integrated data on the content of various physicochemical forms of tritium in air, natural water, and components of aquatic ecosystems at nuclear facility sites. Statistics of lognormal distributions took into account the left truncation, which reflects the effect of finite sensitivity of measurements. The statistics of lognormal distributions were used to obtain estimates for ecosystems of NPP sites at limited sets of data. Specific activities were estimated for various forms of tritium such as HTO (free water), TFWT (tissue free water tritium), and OBT (organically bound tritium). The measurement results show that the specific activity of tritium in the body in bound forms was, as a rule, higher than its specific activity in free water in the ambient environment. Equilibrium concentration ratios (CRs) (partition coefficients of hydrogen) ranged from 1 to about 20. The results obtained by the Radium Institute research team agree with those obtained by the researchers from Canada and France for the specific activity of tritium in different chemical forms in environmental samples.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.265
Teacher spread0.229 · 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.

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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