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Record W2964751360 · doi:10.1073/pnas.1907571116

Airborne concentrations and chemical considerations of radioactive ruthenium from an undeclared major nuclear release in 2017

2019· article· en· W2964751360 on OpenAlexaff
Olivier Masson, Georg Steinhäuser, Dorian Zok, Olivier Saunier, Hristo Angelov, Dinko Babić, Věra Bečková, J. Bieringer, M. Bruggeman, C.I. Burbidge, Sébastien Conil, A. Dalheimer, L.‐E. De Geer, Anne de Vismes Ott, Konstantinos Eleftheriadis, Sybille Estier, Helmut W Fischer, M. Garavaglia, C. Gascó, Krzysztof Gorzkiewicz, Dieter Hainz, Ian Hoffman, Miroslav Hýža, Krzysztof Isajenko, Tero Karhunen, J. Kastlander, Christian Katzlberger, Renata Kierepko, Gert-Jan Knetsch, Júlia Kövendiné Kónyi, M. Lecomte, Jerzy W. Mietelski, Bredo Møller, Sven Poul Nielsen, Jelena D. Krneta-Nikolić, Lidija Nikolovska, I. Penev, Branko Petrinec, Pavel P. Povinec, Rebecca Querfeld, O. Raimondi, Daniela Ransby, W Ringer, Oleksandr Romanenko, R. Rusconi, Paul R. J. Saey, V. Samsonov, B. Šilobritienė, Elena Simion, C. Söderström, Marko Šoštarić, T. Steinkopff, Philipp Steinmann, I. Sýkora, L. Ya. Tabachnyi, Dragana Todorović, E. Tomankiewicz, J. Tschiersch, R. Tsibranski, Michalis Tzortzis, Kurt Ungar, Andreas Vidic, Anica Weller, H. Wershofen, P. Zagyvai, Tamara Zalewska, David García, B. Zorko

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsHealth Canada
FundersNational Oceanic and Atmospheric AdministrationVolkswagen FoundationDeutsche Bundesstiftung Umwelt
KeywordsRutheniumRadioactive wasteRadiochemistryEnvironmental scienceChemistryNuclear chemistry

Abstract

fetched live from OpenAlex

Significance A massive atmospheric release of radioactive 106 Ru occurred in Eurasia in 2017, which must have been caused by a sizeable, yet undeclared nuclear accident. This work presents the most compelling monitoring dataset of this release, comprising 1,100 atmospheric and 200 deposition data points from the Eurasian region. The data suggest a release from a nuclear reprocessing facility located in the Southern Urals, possibly from the Mayak nuclear complex. A release from a crashed satellite as well as a release on Romanian territory (despite high activity concentrations) can be excluded. The model age of the radioruthenium supports the hypothesis that fuel was reprocessed ≤2 years after discharge, possibly for the production of a high-specific activity 144 Ce source for a neutrino experiment in Italy.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.266
Teacher spread0.244 · 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 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

Citations85
Published2019
Admission routes1
Has abstractyes

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