Defeating Radiation Damping and Magnetic Field Inhomogeneity with Spatially Encoded Noise
Bibliographic record
Abstract
A simple NMR experiment capable of providing well resolved spectra under conditions where either radiation damping or static magnetic field inhomogeneity would broaden otherwise high-resolution NMR spectra is introduced. The approach involves using a strong pulsed magnetic field gradient and a selective radio-frequency pulse to encode a predetermined noise pattern into the spatial distribution of magnetization. Following readout in a much smaller field gradient, the noise sequence may be deconvolved from the acquired data and a high-resolution spectrum is obtained, eliminating the effects of either radiation damping or the static field inhomogeneity. In the presence of field inhomogeneity a field map is also obtained from the same single transient. A quasi-two-dimensional version of the experiment eliminates the need for deconvolution and produces improved results with simplified processing, but without requiring a full two-dimensional experiment. Example spectra are shown for both radiation damping and one-dimensional field inhomogeneity with improvement in linewidths of more than a factor of 40.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".