Characterization of the NMR behavior of white matter in bovine brain
Bibliographic record
Abstract
In vitro experiments on 15 white matter samples from five bovine brains were performed on a 1H-NMR spectrometer at 24 degrees C and 37 degrees C. The average myelin water fractions (MWFs) were 10.9% and 11.8% for samples at 24 degrees C and 37 degrees C, respectively. The T1 relaxation time at 37 degrees C was found to be 830 ms, exhibiting monoexponential behavior. A four-pool model including intra/extracellular (IE) water, myelin water, nonmyelin tissue, and myelin tissue was proposed to simulate the NMR behavior of bovine white matter. A cross-relaxation correction was introduced to compensate for shifting of the measured data points and T2 times over the duration of the Carr-Purcell-Meiboom-Gill (CPMG) measurement due to cross relaxation. This correction was found to be slight, providing evidence that MWFs measured using a multiecho technique are near physical values. At 24 degrees C the cross-relaxation times between myelin tissue and myelin water, myelin water and IE water, and IE water and nonmyelin tissue were found to be approximately 227, 2064, and 402 ms, respectively. At 37 degrees C these same cross-relaxation times were 158, 1021, and 170 ms, respectively. The exchange rate between myelin water and myelin was found to be 11.8 s-1 at 37 degrees C, while the exchange rate between IE water and nonmyelin tissue was found to be 6.8 s-1. These exchange rates are of similar magnitude, which indicates that the interaction between IE water and nonmyelin tissue cannot be ignored.
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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 | 0.000 | 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 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".