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Record W2057009284 · doi:10.1039/c3pc90005c

The positive muon and μSR spectroscopy: powerful tools for investigating the structure and dynamics of free radicals and spin probes in complex systems

2013· article· en· W2057009284 on OpenAlexaff
Iain McKenzie

Bibliographic record

VenueAnnual Reports Section C (Physical Chemistry) · 2013
Typearticle
Languageen
FieldEngineering
TopicMuon and positron interactions and applications
Canadian institutionsSimon Fraser UniversityTRIUMF
Fundersnot available
KeywordsMuon spin spectroscopyRadicalChemistrySpectroscopyRelaxation (psychology)Chemical physicsMuonElectron paramagnetic resonanceNuclear magnetic resonance spectroscopyNuclear magnetic resonanceOrganic chemistryNuclear physicsPhysics

Abstract

fetched live from OpenAlex

The positive muon (μ+) can be incorporated into free radicals where it acts as a probe of the structure and dynamics. The muoniated radicals are characterized by a series of magnetic resonance techniques known as μSR for muon spin rotation, resonance and relaxation spectroscopy. In this review it is shown how μSR can be used to obtain information about the structure, dynamics, and local environments of transient radicals in solids like zeolites, in solution or even in exotic solvents like supercritical water. It will also be demonstrated that muoniated radicals can be used as probes in complex systems, such as rod-like and discotic liquid crystals, bilayers and polymers, where they have advantages over traditional spin labelling.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.014

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 studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.243
Teacher spread0.237 · 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
GenreMethods

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

Citations80
Published2013
Admission routes1
Has abstractyes

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