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Record W7119020931 · doi:10.25545/vukfys

A Simple Portable Magnetic Resonance Technique for Characterizing Circular Couette Flow of Non-Newtonian Fluids

2025· dataset· W7119020931 on OpenAlexaff
William Selby, Phil Garland, Igor V. Mastikhin

Bibliographic record

VenueUNB Dataverse · 2025
Typedataset
Language
Field
Topic
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsCouette flowSIGNAL (programming language)Flow (mathematics)Resonance (particle physics)Magnetic fieldRheologyExcitationExcited state

Abstract

fetched live from OpenAlex

This repository contains all raw data files and processing scripts associated with the paper published in the Journal of Magnetic Resonance entitled “A Simple Portable Magnetic Resonance Technique for Characterizing Circular Couette Flow of Non-Newtonian Fluids.” Abstract: In this work, we expand on past portable magnetic resonance flow methods and propose a novel method for characterizing circular (laminar) Couette flow of non-Newtonian fluids. Symmetry of the flow system combined with a constant magnetic field gradient leads to phase interference, affecting the signal magnitude, and net phase cancellation when averaging across the excited slice, preventing the use of phase-sensitive methods. Therefore, we utilize the dependence of signal magnitude at variable echo times and shear rates to characterize rheological properties. Theoretical equations governing the velocity distributions of fluids that obey a simple power-law model are used to obtain integral expressions for signal magnitude. Integral expressions can be simplified by approximating a thin excited slice or complete excitation of the Couette cell depending on experimental parameters. With simple data acquisition and analysis procedures employed, our measurements of the flow behavior indices of non-Newtonian xanthan gum dispersions are in close agreement with conventional rheological magnetic resonance measurements.

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), Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.275
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0030.004
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0060.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.003

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 head0.011
GPT teacher head0.260
Teacher spread0.249 · 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 designNot applicable
Domainnot available
GenreDataset

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 routes1
Has abstractyes

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