MétaCan
Menu
Back to cohort

Isobar Attenuation Using Anion–Gas Reactions for Accelerator Mass Spectrometry and Application to <sup>36</sup>Cl

2010· article· en· W2082093077 on OpenAlexaff
J. Eliades, Xiaolei Zhao, W.E. Kieser, A.E. Litherland

Bibliographic record

VenueGeostandards and Geoanalytical Research · 2010
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIsobarAccelerator mass spectrometryIonChemistryMass spectrometryIon sourceQuadrupoleIsobaric processIon beamAnalytical Chemistry (journal)Quadrupole mass analyzerAtomic physicsBeam (structure)Nuclear physicsPhysicsNucleon

Abstract

fetched live from OpenAlex

Preliminary tests of a prototype radio‐frequency quadrupole (RFQ) collision cell system, known as an isobar separator for anions (ISA), for the removal of isobaric interferences for accelerator mass spectrometry (AMS) and for studies of anion–gas interactions are reported. The ISA decelerated a mass‐analysed beam of anions from an energy (∼ 20 keV) typically generated by an AMS ion source to &lt; 10 eV. RFQs and electrostatic lenses then guided the ions through the collision cell where ion‐gas collisions reduced both the energy and energy spread of the ion beam (cooled the ions) and ion‐gas reactions attenuated most of the unwanted isobars. The anions were then re‐accelerated to their original energy for injection into the rest of the AMS system. With the ISA installed on a full 3 MV AMS system, attenuations of 32 S ‐ , 12 C 3 ‐ and 39 K ‐ by six, seven and greater than ten orders of magnitude, respectively were achieved using 0.7–1 Pa NO 2 gas in the collision cell, while maintaining approximately 10–30% of the chlorine anion transmission. A further measurement of a 36 Cl/Cl = 4.1 × 10 ‐11 RM is also described. The results suggest that the 36 Cl/Cl lower detection limit of the current system was 10 ‐14 –10 ‐15 for samples that could be prepared with S/Cl ratios below 10 μg g ‐1 .

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.636
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.039
GPT teacher head0.388
Teacher spread0.349 · 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.

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

Citations11
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueGeostandards and Geoanalytical ResearchSame topicMass Spectrometry Techniques and ApplicationsFrench-language works237,207