Quantitative <sup>1</sup>H NMR with External Standards: Use in Preparation of Calibration Solutions for Algal Toxins and Other Natural Products
Bibliographic record
Abstract
We examine the use of external standards for quantitative measurement by 1H NMR of solution concentrations of natural products and other low molecular weight, hydrogen-containing compounds and show that precision and accuracy ca. 1% is obtainable with a commercial 11.7 T spectrometer when standards and analytes are contained in separate but identical sealed precision glass NMR tubes. Numerous factors contributing to the intensity of the NMR signals are evaluated. Precise measurements of 360 degrees pulse lengths for each sample provide direct corrections for variations in probe Q-factor that enable samples in different solvents to be compared, provided single-coil excitation and detection is used throughout. Samples need not be prepared in deuterated solvents if the 1H spectra of the solvents are simple enough for peak suppression by presaturation. The approach is particularly suitable for hazardous materials kept in sealed tubes and for the preparation of certified calibration solution reference materials for use with LC-MS and other techniques where deuterated solvents should be avoided.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".