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Record W4412731124 · doi:10.1016/j.mrl.2025.200229

Spin-echo measurements for capillary rheometry at low field

2025· article· en· W4412731124 on OpenAlexafffund
Sebastian Richard, Bruce J. Balcom, Benedict Newling

Bibliographic record

VenueMagnetic Resonance Letters · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRheometryEcho (communications protocol)Field (mathematics)Capillary actionNuclear magnetic resonanceSpin (aerodynamics)Materials sciencePhysicsComputer scienceComposite materialThermodynamicsMathematicsPolymer

Abstract

fetched live from OpenAlex

A single spin-echo, acquired in the presence of a constant magnetic field gradient, has a phase proportional to the average velocity of the sample and an amplitude determined by the distribution of velocities for laminar flow in a pipe. If we make assumptions about symmetry, it is therefore possible to reconstruct a velocity profile from a series of spin echoes acquired with different echo times, . The velocity profile encompasses a range of shear stresses and so describes the shear-rate dependence of the fluid viscosity, making this a rapid, non-invasive rheometric measurement. The appeal of this approach lies in its simplicity: a constant, uniform magnetic field gradient can be readily constructed using low-field permanent magnets and the resulting magnetic resonance instrument is relatively cheap and easily sited. In order to extend the range of fluids to which such a rheometer can be applied, we have designed a pre-measurement polarization unit to maximize the polarization of fluids with a long , such as aqueous solutions.

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 score0.149
Threshold uncertainty score0.539

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 head0.010
GPT teacher head0.301
Teacher spread0.291 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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