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Record W4386330452 · doi:10.21203/rs.3.rs-3299267/v1

Estimation of relaxation times during free evolution from the SECSY signal of an electron-nuclear spin-coupled system in a γ-irradiated malonic acid single crystal

2023· preprint· en· W4386330452 on OpenAlexafffund
Hamid Reza Salahi, Sushil K. Misra

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicElectron Spin Resonance Studies
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCoherence (philosophical gambling strategy)Relaxation (psychology)PhysicsIrradiationElectronSpin (aerodynamics)Single crystalCrystal (programming language)Nuclear magnetic resonanceElectron paramagnetic resonanceMalonic acidAtomic physicsResonance (particle physics)Free induction decayChemistryMolecular physicsSpin echoQuantum mechanicsMagnetic resonance imaging

Abstract

fetched live from OpenAlex

Abstract The relaxation times T2,' characterizing the allowed and T2'', characterizing the forbidden and coherence cross resonances, during free evolutions over the coherent pathways p = ±1 are estimated from the SECSY (Spin Echo Correlation Spectroscopy) signal of the electron-nuclear spin-coupled system in a γ-irradiated malonic acid single crystal. This is accomplished by fitting the intensities of the two main peaks in the Fourier transform of the SECSY signal reported by Lee, Patyal and Freed (J. Chem. Phys. 98, 3665 (1993)) to T2' and T2''. The values of the fitted relaxation times T2'=500 ns, T2"=50,000 ns, reveal that the relaxation via the allowed resonance is two orders of magnitude faster than that via the forbidden and cross resonances. Full details of the calculation exploiting the Liouville von Neumann equation are presented. PACS: 76.30.-v, 76.70.Dx

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.314
Teacher spread0.293 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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