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Pore-Size Measurement from Eigenvalues of Magnetic Resonance Relaxation

2021· article· en· W3199033780 on OpenAlexafffund
Armin Afrough, Florea Marica, Bryce MacMillan, Bruce J. Balcom

Bibliographic record

VenuePhysical Review Applied · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsUniversity of New Brunswick
FundersDanish Hydrocarbon Research and Technology Centre, Technical University of DenmarkNatural Sciences and Engineering Research Council of Canada
KeywordsRelaxation (psychology)Nuclear magnetic resonanceEigenvalues and eigenvectorsResonance (particle physics)T2 relaxationMaterials sciencePhysicsCondensed matter physicsMagnetic resonance imagingAtomic physicsQuantum mechanicsMedicinePsychologyNeuroscience

Abstract

fetched live from OpenAlex

Nonground eigenvalues are widely disregarded in magnetic resonance relaxation measurements of porous media due to difficulties involved in their measurement, detection, and the derivation of physically meaningful parameters from them. Such nonground eigenvalues may be experimentally observed in relaxation measurements, such as the relaxation correlation of ${T}_{1}\ensuremath{-}{T}_{2}$, and yield information on the pore size and surface relaxivity of porous media without calibration through other independent measurements. Nonground eigenvalue analysis of ${T}_{1}\ensuremath{-}{T}_{2}$ measurements on Berea sandstone undertaken at three static magnetic fields produces pore sizes consistent with those obtained through x-ray microtomography and SEM measurements. Similar agreement is found for a Bentheimer sandstone with a more complex pore geometry. A phase-encoding imaging variant of this method measures the imbibition confinement-size profile in Berea sandstone. It is suggested that the existence of nonground eigenmodes may be much more prevalent in simple magnetic resonance relaxation measurements than previously considered. Therefore, it is possible to measure pore size by matching numerical Brownstein-Tarr solutions with those of experiments in a wide variety of samples and magnetic resonance methods.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.645
Threshold uncertainty score0.712

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)0.0010.000

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 head0.019
GPT teacher head0.319
Teacher spread0.301 · 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 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

Citations15
Published2021
Admission routes2
Has abstractyes

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