Strategy for the spectral filtering of myo‐inositol and other strongly coupled spins
Bibliographic record
Abstract
A multiple quantum filter strategy is presented for spectrally discriminating metabolites with strongly coupled spins from those whose spins are either uncoupled or weakly coupled. The strategy also includes a means for selectively suppressing the background multiplets of metabolites that also have strongly coupled spins. As a demonstration of its efficacy at 3.0 T, the strategy is shown to enhance by a factor of approximately 5 the signal-to-background ratio of the myo-inositol band at 3.6 ppm relative to that in response to a PRESS sequence with the same sequence timings. This is done by eliminating the uncoupled resonance of glycine and the weakly coupled multiplets of glutamate and glutamine, and by selectively suppressing the strongly coupled taurine multiplet 3-fold. The macromolecular background was effectively removed through its transverse decay over 105 ms. The associated cost of gaining the signal to background enhancement is a drop in signal yield by a factor of 0.75 relative to PRESS at the same timings. The myo-inositol signal to noise ratio was nevertheless maintained by the filter at approximately 12.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".