Mean residence times and characteristics of humic substances extracted from a Taiwan soil
Bibliographic record
Abstract
Humic substances are well known for their long-term persistence in soil environments. The relationship between the mean residence times (MRT) and characteristics of humic substances extracted from a soil with highorganic matter (OM) content in Taiwan was investigated. The MRTs of the soil organic matter (SOM) and its humic substances extracted from the soil samples taken from three depths (0–20, 40–60, and 70–150 cm) of a soil profile were determined by 14C-dating procedures. Moreover, the humic substances were subjected to elemental analysis and investigation by electron spin resonance (ESR), Fourier transform infrared (FTIR), and solid-state 13C nuclear magnetic resonance (13C NMR) spectroscopies. The ranges of the MRT of fulvic acids (FA) (MW < 1000), FA (MW > 1000), humic acid (HA) (MW > 1000), and humins (MW > 1000) were 143 ± 110 to 1740 ± 60, 213 ± 120 to 1690 ± 200, 253 ± 60 to 2200 ± 40, and 293 ± 40 to 2173 ± 70 yr, respectively. The higher standard deviations of the means of determined MRTs of FA (MW < 1000) and FAs (MW > 1000) may be due to their lability. Further, the MRTs of the FAs (MW < 1000), FAs (MW > 1000), HAs (MW > 1000), and humins (MW > 1000) increased with increasing soil profile depth, indicating the slow biological and chemical degradations of humic substances in the deeper layers. The elemental composition and spectroscopic properties of FTIR, 13C NMR, and ESR of humic substances did not change significantly with their MRTs. The MRTs in the range observed in this study were apparently long enough to render humic substances a high degree of chemical stability. Key words: Humic substances, mean residence times, ESR, FTIR, 13C NMR, humin
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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".