Quantitative Characterization of a Hardwood Milled Wood Lignin by Nuclear Magnetic Resonance Spectroscopy
Bibliographic record
Abstract
The structure of Eucalyptus grandis milled wood lignin (MWL) was investigated by 2D 1H-13C HSQC, HMQC, and 1H-1H TOCSY correlation NMR techniques and by quantitative 13C NMR as well as by the permanganate oxidation degradation technique. The combination of 2D NMR and quantitative 13C NMR spectroscopy of nonacetylated and acetylated lignin preparations allowed reliable identification and calculation of the amount of different lignin structures. About 85% of side-chain moieties were estimated on the structural level. This information was substantiated by data on the quantity of various functional groups and interunit linkages as a whole. A modified method for calculation of the h:g:s ratio has been suggested and compared with previously suggested approaches. E. grandis MWL has been determined to have an h:g:s ratio of 2:36:62. The amounts of various phenolic/etherified noncondensed/condensed guaiacyl and syringyl moieties were approximately estimated. E. grandis MWL contained approximately 0.60/Ar of beta-O-4 moieties along with small amounts of other structural units such as pino/syringyresinol (0.03/Ar), phenylcoumaran (0.03/Ar), and spirodienone (0.05/Ar). The degree of condensation was estimated at approximately 21%; the main condensed structures are 4-O-5 moieties (approximately 0.09/Ar). The structure of E. grandis MWL was compared with those of other lignin preparations isolated from various hardwoods.
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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 | 0.001 | 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) | 0.001 | 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".