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Record W2751294439 · doi:10.1007/s10967-017-5446-0

A new bomb-combustion system for tritium extraction

2017· article· en· W2751294439 on OpenAlexaff
Richard Ian Marsh, Ian W. Croudace, Phillip E. Warwick, Natasha Cooper, Nadereh St-Amant

Bibliographic record

VenueJournal of Radioanalytical and Nuclear Chemistry · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsCanadian Nuclear Safety Commission
FundersCulham Centre for Fusion Energy
KeywordsCombustionPyrolysisExtraction (chemistry)TritiumPlutoniumChemistryRadioactive wasteOxygenMatrix (chemical analysis)Waste managementRadiochemistryNuclear engineeringNuclear chemistryChromatographyNuclear physicsOrganic chemistry

Abstract

fetched live from OpenAlex

Quantitative extraction of tritium from a sample matrix is critical to efficient measurement of the low-energy pure beta emitter. Oxidative pyrolysis using a tube furnace (Pyrolyser) has been adopted as an industry standard approach for the liberation of tritium (Warwick et al. in Anal Chim Acta 676:93–102, 2010) however pyrolysis of organic-rich materials can be problematic. Practically, the mass of organic rich sample combusted is typically limited to <1 g to minimise the possibility of incomplete combustion. This can have an impact on both the limit of detection that can be achieved and how representative the subsample is of the bulk material, particularly in the case of heterogeneous soft waste. Raddec International Ltd (Southampton, UK), in conjunction with GAU-Radioanalytical, has developed a new high-capacity oxygen combustion bomb (the Hyperbaric Oxidiser; HBO2) to address this challenge. The system is capable of quantitatively combusting samples of 20–30 g under an excess of oxygen, facilitating rapid extraction of total tritium from a wide range sample types.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score0.501

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)0.0000.000

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 head0.009
GPT teacher head0.245
Teacher spread0.235 · 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.

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

Citations5
Published2017
Admission routes1
Has abstractyes

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