The Identification of Plant Derived Structures in Humic Materials Using Three-Dimensional NMR Spectroscopy
Bibliographic record
Abstract
Here we demonstrate the application of 3-D NMR spectroscopy to structural studies of humic substances, the most abundant of organic compounds on earth. The increased spectral dispersion provided by the additional dimension is proven to be highly advantageous in separating the overlapping signals observed in 2-D spectra. Assignments of the major aliphatic structures and selected aromatic moieties are given as examples. We find that in a forest soil fulvic acid the major aliphatic materials are likely derived from leaf cuticles and further demonstrate that lignin signatures can be identified among the aromatic species. Once identified from the 3-D spectra, these structures can be assigned using the partial information available in 2-D, and in some cases, in the 1-D spectra. These signals are demonstrated to be characteristic to given samples of natural organic matter, and the case is made for their use as indicators of terrestrial biomarkers in mixtures of compounds with unknown origins.
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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) | 0.000 | 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".