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Record W2569534687 · doi:10.1139/p02-108

Single-ion mass spectrometry at 100 ppt and beyond

2002· article· en· W2569534687 on OpenAlexvenueno aff
Simon Rainville, James K. Thompson, David E. Pritchard

Bibliographic record

VenueCanadian Journal of Physics · 2002
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsPhysicsPenning trapIon trapCyclotronAtomic physicsIonMass spectrometryIon trappingAtomic massFourier transform ion cyclotron resonanceMeasure (data warehouse)Trap (plumbing)Nuclear physics

Abstract

fetched live from OpenAlex

Using a Penning trap single-ion mass spectrometer, we measured the atomic masses of 14 isotopes with a fractional accuracy of ~10–10. The precision on these measurements was limited by the temporal fluctuations of our magnetic field. By trapping two different ions in the same Penning trap at the same time, we have recently been able to virtually eliminate that source of error. We can now simultaneously measure the ratio of the two ion's cyclotron frequencies (from which we obtain their atomic mass ratio) with a precision of about 10–11 in only a few hours. To perform these comparisons, we must be able to measure and control all three normal modes of motion of each ion — cyclotron, axial, and magnetron — and have developed novel techniques to do so. This new technique shows promise of expanding the precision of mass spectrometry by an order of magnitude beyond the current state-of-the-art. PACS Nos.: 32.10Bi, 06.20Jr, 06.30Dr, 07.75+h, 07.77-n

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 score0.011
Threshold uncertainty score0.036

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.006

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 head0.017
GPT teacher head0.217
Teacher spread0.200 · 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
Published2002
Admission routes1
Has abstractyes

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