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Record W4408318535 · doi:10.1016/j.ijms.2025.117433

3 MV accelerator mass spectrometry measurements of 36Cl using the Isobar Separator for Anions

2025· article· en· W4408318535 on OpenAlexaff
Erin L. Flannigan, W.E. Kieser, Carley Crann, Christof Vockenhuber, B.B.A. Francisco

Bibliographic record

VenueInternational Journal of Mass Spectrometry · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsChemistryIsobarSeparator (oil production)Accelerator mass spectrometryMass spectrometryIsobaric processAnalytical Chemistry (journal)Nuclear physicsRadiochemistryChromatography

Abstract

fetched live from OpenAlex

A second low-energy injection line containing the Isobar Separator for Anions (ISA), a radiofrequency quadrupole reaction cell system, was installed on the 3 MV tandem accelerator system at the A. E. Lalonde (AEL) accelerator mass spectrometry (AMS) Laboratory. The suppression of 36 S via anion-gas reaction with NO 2 was evaluated for measurements of 36 Cl reference materials and a dilution series, using a 3 MV AMS system. The dilution series, with 36 Cl/Cl ratios ranging from 10 -11 to 10 -15 , were measured in comparison with external measurement. 36 Cl/Cl blank levels of (7 ± 4) x10 -15 were reached. While ISA-AMS is not currently able to achieve sufficient separation for most 36 Cl applications, these measurements show progress towards routine measurement of 36 Cl and demonstrate the steps required to validate such measurements on lower energy AMS systems. • 3 MV AMS and a radiofrequency quadrupole reaction cell were used to measure 36 Cl. • The isobar 36 S - was suppressed by 7 orders of magnitude using reactions with NO 2 . • Dilutions series with 36 Cl/Cl ratios ranging from 10 -11 to 10 -15 and a blank level of 7 x10 -15 were measured. • Progress has been made towards using the Isobar Separator for Anions to the routine measurement of 36 Cl on lower energy AMS systems.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.483

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 science0.0010.000
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 head0.032
GPT teacher head0.335
Teacher spread0.303 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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