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Record W2946370595 · doi:10.1021/acs.jpcb.9b02930

Hydrogen-Atom Addition to Nucleobases in the Solid State: Characterization of the Corresponding Muoniated Radicals Using μSR

2019· article· en· W2946370595 on OpenAlexafffund
Iain McKenzie

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2019
Typearticle
Languageen
FieldEngineering
TopicMuon and positron interactions and applications
Canadian institutionsSimon Fraser UniversityTRIUMF
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsRadicalChemistryNucleobaseThymineMuoniumGuanineMuonHyperfine structurePhotochemistryCrystallographyHydrogenAtomic physicsDNAPhysics

Abstract

fetched live from OpenAlex

The radicals formed by muonium (Mu) addition to four nucleobases (adenine, guanine, cytosine, and thymine) have been characterized by avoided level-crossing muon spin resonance (ALC-μSR). Mu is considered to be a light isotope of the hydrogen atom, and the muoniated radicals observed by ALC-μSR are isotopomers of the radicals initially produced by H addition to the nucleobases. The observed radicals have been assigned by considering the relative energies of the possible radicals reported in the literature and comparing the experimental muon and proton hyperfine coupling constants with values from previously reported electron paramagnetic resonance and ab initio calculations that have been scaled to account for the larger magnetic moment of the muon and its lighter mass compared with the proton. Mu addition is observed to occur only at secondary carbons of the purine rings in adenine and guanine. Mu adds to C8 and C2 of adenine with the relative amount being ∼70:30%, and Mu adds exclusively to C8 of guanine. Mu addition is predominantly to the secondary carbons of the pyrimidine ring in cytosine (C5 and C6 with relative yields ∼80:20%) with a small amount of addition at N3. Mu adds to both the secondary C6 and tertiary C5 in thymine with approximately equal yields as well as the O4 adduct being a minor product.

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 score0.027
Threshold uncertainty score0.145

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 science0.0000.000
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 head0.007
GPT teacher head0.248
Teacher spread0.241 · 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

Citations10
Published2019
Admission routes2
Has abstractyes

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