<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si43.svg" display="inline" id="d1e1135"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msub> </mml:math> – <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si44.svg" display="inline" id="d1e1145"> <mml:msubsup> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>∗</mml:mo> </mml:mrow> </mml:msubsup> </mml:math> relaxation correlation measurement
Bibliographic record
Abstract
Relaxation and relaxation-diffusion correlation measurements have emerged as essential tools for magnetic resonance of materials. Examples of correlation measurements include the T 1 – T 2 , the T 2 – D , and the T 1 – T 2 ∗ variants. In this paper, we describe the implementation and validation of a T 2 – T 2 ∗ relaxation correlation measurement. It is shown that this technique effectively distinguishes microscopic environments dominated by local field inhomogeneity from those dominated by nuclear spin-spin interactions. The method is demonstrated in simulation and in glass bead packs. • A new relaxation-time-constant correlation measurement, T 2 – T 2 ∗ , is described. • Relaxation-time-constant correlation measurements are demonstrated in glass bead packs for two glass bead systems with different surface relaxivities.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.599 | 0.697 |
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".