A Simple Portable Magnetic Resonance Technique for Characterizing Circular Couette Flow of Non-Newtonian Fluids
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.108 | 0.120 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".