A comparison of magnetic resonance methods for spatially resolved<i>T</i><sub>2</sub>distribution measurements in porous media
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Bibliographic record
Abstract
Naturally occurring porous media are usually characterized by a distribution of pore sizes. If the material is fluid saturated, the 1H magnetic resonance (MR) signal depends on the pore size, the surface relaxivity and the fluid itself. Measurement of the transverse relaxation time T2 is a well-established technique to characterize material samples by means of MR. T2 distribution measurements, including T2 distribution mapping, are widely employed in clinical applications and in petroleum engineering. T2 distribution measurements are the most basic measurement employed to determine the fluid-matrix properties in MR core analysis. Three methods for T2 distribution mapping, namely spin-echo single point imaging (SE-SPI), DANTE-Z Carr–Purcell–Meiboom–Gill (CPMG) and adiabatic inversion CPMG are compared in terms of spatial resolution, minimum observable T2 and sensitivity. Bulk CPMG measurement is considered to be the gold standard for T2 determination. Bulk measurement of uniform samples is compared to the three spatially resolved measurements. SE-SPI is an imaging method, which measures spatially resolved T2s in samples of interest. A variant is introduced in this work that employs pre-equalized magnetic field gradient waveforms and is therefore able to measure shorter T2s than previously reported. DANTE-Z CPMG and adiabatic inversion CPMG are faster, non-imaging, local T2 distribution measurements. The DANTE-Z pulse train and adiabatic inversion pulse are compared in terms of T1 or T2 relaxation time effects during the RF pulse application, minimum pulse duration, requisite RF pulse power, and inversion profile quality. In addition to experimental comparisons, simulation results are presented.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it