Monitoring transformation of two tropical lignocellulosics and their lignins after residence in Benin soils
Bibliographic record
Abstract
Thermally assisted Hydrolysis and Methylation (THM), and 2D-heteronuclear single quantum coherence nuclear magnetic resonance (2D HSQC NMR) spectroscopy were used to monitor the transformation of ramial chipped wood (RCW) from Gmelina arborea and Sarcocephalus latifolius, together with their organosolv lignins, following soil incubation in Benin (West Africa). Mesh litterbags containing RCW were buried in soils (10 cm depth) and were retrieved after 0, 6, 12 and 18 months of field incubation. Chemical analysis showed that total carbohydrate content decreased, while total lignin content increased as RCW decomposition progressed. Ash and mineral content of RCW increased significantly after 18 months of decomposition in soil. Significant N-enrichment of the RCW was determined following 18 months incubation in soils, reaching 2.6 and 1.9 times the initial N-content for G. arborea and S. latifolius. Results of THM showed that the S + G sum, corresponding to lignins, increased with RCW residence time in the soils, in contrast to the response of compounds derived from carbohydrates, the sum of which decreased. Remarkably, lignin interunit linkages, most notably β-O-4' aryl ethers, β-β' resinol, β-5' phenylcoumaran and p-PCA p-coumarate, survived after 18 months in the soil, despite their gradual decrease over the duration of the experiment.
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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".