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Production of Radioactive Molecular Ions in Radiofrequency Quadrupole Gas-Reaction Cells

2022· article· en· W4224433816 on OpenAlexaff
C.R.J. Charles, F. Ames, O. Kester, S. Malbrunot-Ettenauer, C. Babcock, Brad Schultz, Cameron Peters, Erin L. Flannigan, Jean‐François Alary, Aurelia Laxdal, P. Kunz, J. Lassen, Andrea Teigelhoefer, P. J. A. McCausland, R. L. Flemming

Bibliographic record

VenueJournal of Physics Conference Series · 2022
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsWestern UniversityUniversity of OttawaUniversity of WaterlooTRIUMF
Fundersnot available
KeywordsIonPhysicsHeavy ionNuclear physicsMoleculeQuadrupoleIon sourceAtomic physicsChemistryNuclear engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Limited types of radioactive molecules (RM) can be made inside hot-cavity targets at ISOL facilities like TRIUMF. However, extreme conditions in these targets present formidable unsolved challenges to efficient production and delivery of RM’s. Here we propose using RFQ gas-reaction cells to produce RM from radioactive ion beams (RIB) by room temperature RIB-gas chemical reactions at eV energies. Two options are possible: (1) using an ion reaction cell (IRC) that is a linear RFQ ion guide and reaction cell used as an ‘on-line ion source’, and (2) using the ARIEL RFQ cooler-buncher (ARQB). RFQ gas-cells are a controllable and efficient method to produce RM from chemical reactants that cannot be used in ISOL targets. This ‘online chemistry’ offers a way to enable groundbreaking Beyond Standard Model (BSM) physics research, using a wide diversity of new rare and exotic RM beams that would be difficult or impossible to produce in hot-cavity targets.

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 score0.072
Threshold uncertainty score0.385

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 communication0.0000.001
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 head0.012
GPT teacher head0.214
Teacher spread0.203 · 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
Published2022
Admission routes1
Has abstractyes

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