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Record W2540388114 · doi:10.1515/ract-2016-2605

Extraction of Tc(VII) and Re(VII) on TRU resin

2016· article· en· W2540388114 on OpenAlexaff
Nicolas Guérin, Rémi Riopel, Sheila Kramer-Tremblay, Nimal De Silva, Jack Cornett, X. Dai

Bibliographic record

VenueRadiochimica Acta · 2016
Typearticle
Languageen
FieldChemistry
TopicRadioactive element chemistry and processing
Canadian institutionsUniversity of OttawaCanadian Nuclear Laboratories
Fundersnot available
KeywordsChemistryElutionExtraction (chemistry)BoilingChromatographyNuclear chemistryVolume (thermodynamics)Analytical Chemistry (journal)Organic chemistry

Abstract

fetched live from OpenAlex

Abstract TRU resin can be used to rapidly and selectively extract Tc(VII) and Re(VII). The retention capacity curves of Tc(VII) and Re(VII) for HNO3, HCl, H2SO4 and H3PO4 solutions were studied and prepared. Tc(VII) and Re(VII) were simultaneously extracted in 2 M H2SO4 and 1.5 M H3PO4 and were effectively separated from Mo(VI) and Ru(III). Tc(VII) and Re(VII) remained strongly bonded to the resin even after washing using a large volume of 2 M H2SO4 at a relatively high flow rate. Also, they were both completely eluted from the resin using 15 mL of near boiling water, an eluent directly compatible for ICP-MS instrument measurements.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.015
GPT teacher head0.262
Teacher spread0.247 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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