Quantitative <sup>13</sup>C NMR Analysis of Lignins with Internal Standards
Bibliographic record
Abstract
Novel protocols for acquiring quantitative 13 C NMR spectra of lignins have been developed using the internal reference compounds 1,3,5-trioxane and pentafluorobenzene. Trioxane offers a convenient internal standard for collecting inverse gated proton decoupled 13 C NMR spectra for lignins, whereas pentafluorobenzene can be used to provide information on the amount of methine carbon using the DEPT experiment. In each case, the internal reference compounds provide single, un-overlapped sharp signals in the middle of the spectral region, permitting facile integration. These integrals could be used to determine the amounts of different structural features of lignins, expressed in absolute units of millimoles per gram. The optimum parameters for these experiments were validated for a variety of spectrometer platforms, and standard errors were determined for different spectral areas using lignin model compounds and “standard” lignins. In addition, the data derived for the International Round Robin “standard” lignins showed good agreement with the data from quantitative 31 P NMR spectroscopy and published data, obtained by independent laboratories using independent methods of analysis. Keywords: Lignin; nuclear magnetic resonance spectroscopy (NMR); inverse gated proton decoupled carbon-13 NMR spectroscopy; distortionless enhancement by polarization transfer (DEPT); internal standard; acquisition protocol; International Round Robin lignins; relaxation reagent
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".