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Record W1985752685 · doi:10.1103/physreva.73.022721

Nuclear relaxation of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mmultiscripts><mml:mi>He</mml:mi><mml:none/><mml:none/><mml:mprescripts/><mml:none/><mml:mn>3</mml:mn></mml:mmultiscripts></mml:mrow></mml:math>in the presence of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>NO</mml:mi></mml:mrow></mml:math>

2006· article· lv· W1985752685 on OpenAlexafffund
G. Archibald, Elana Brief, Chao Lei, T. Pausak, M. E. Hayden

Bibliographic record

VenuePhysical Review A · 2006
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicAtomic and Subatomic Physics Research
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsParamagnetismRelaxation (psychology)Nuclear magnetic resonanceCondensed matter physics

Abstract

fetched live from OpenAlex

By virtue of the fact that its low-lying $^{2}\mathrm{\ensuremath{\Pi}}_{3∕2}$ state is paramagnetic, nitric oxide $(\mathrm{NO})$ can be an effective agent for inducing nuclear spin relaxation during isolated binary collisions with other species. At the same time, the strong coupling between the electronic angular momentum and the internuclear axis of this particular molecule leads to a situation in which its effective magnetic moment depends critically on molecular motions that take place on the time scale of the collision. Here we present the results of an investigation in which the NMR-detected longitudinal nuclear relaxation rate ${T}_{1}^{\ensuremath{-}1}$ of room temperature $^{3}\mathrm{He}$ gas adulterated with $\mathrm{NO}$ was measured as a function of $\mathrm{NO}$ density $([\mathrm{NO}])$ in two different magnetic fields. We find ${T}_{1}^{\ensuremath{-}1}=0.0502(3)[\mathrm{NO}]\phantom{\rule{0.3em}{0ex}}{\mathrm{s}}^{\ensuremath{-}1}$ at $1.50\phantom{\rule{0.3em}{0ex}}\mathrm{T}$, and ${T}_{1}^{\ensuremath{-}1}=0.0506(3)[\mathrm{NO}]\phantom{\rule{0.3em}{0ex}}{\mathrm{s}}^{\ensuremath{-}1}$ at $2.35\phantom{\rule{0.3em}{0ex}}\mathrm{T}$, where $[\mathrm{NO}]$ is expressed in amagat. Under these conditions approximately two-thirds of the $\mathrm{NO}$ molecules occupy the diamagnetic $^{2}\mathrm{\ensuremath{\Pi}}_{1∕2}$ ground state and one-third occupy the paramagnetic $^{2}\mathrm{\ensuremath{\Pi}}_{3∕2}$ state. Our data can be understood in terms of a semiclassical treatment of collision dynamics that involves the paramagnetic moment autocorrelation function.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0020.003
Open science0.0050.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0230.005

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 head0.266
Teacher spread0.245 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations3
Published2006
Admission routes2
Has abstractyes

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