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Record W3120578917 · doi:10.1007/s10967-020-07500-2

Measurement of k0 values for europium, lutetium and iridium at FRM II with a very well thermalized neutron spectrum

2021· article· en· W3120578917 on OpenAlexaff
X. Li, R. van Sluijs, G. Kennedy

Bibliographic record

VenueJournal of Radioanalytical and Nuclear Chemistry · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsPolytechnique Montréal
FundersTechnische Universität München
KeywordsLutetiumEuropiumIridiumNuclideAnalytical Chemistry (journal)IsotopeChemistryNuclear dataNeutronMaterials sciencePhysicsNuclear physicsYttriumIon

Abstract

fetched live from OpenAlex

Abstract The k0 values of 6 non-1/v nuclides (152Eu, 152mEu, 154Eu, 177Lu, 192Ir and 194Ir) were determined using the extended Høgdahl formalism at the research reactor FRM II with very high f values. Standards were irradiated in 4 channels at different local temperatures between 40 °C and 55 °C measured using temperature sensitive irreversible labels. A good agreement with the recommended values was found for 152Eu, 154Eu and 177Lu using the original g(Tn) factors by Gryntakis, however, the k0 values for 152mEu in this work were 7% higher. New k0 values were also determined using the g(Tn) factors by Van Sluijs. Differences up to 6% were found for Eu isotopes compared with the recommended values. The recommended k0 values for 192Ir and 194Ir could be confirmed using g = 1. The theoretical k0 values for 177Lu were calculated using new nuclear data. They are up to 6% less than the recommended values. The present k0 values determined in this work showed a similar trend. The influence of different g(Tn) factors on the determination of the k0 values was investigated.

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)0.001
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.205
Teacher spread0.198 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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