Humic Acids of Leached Chernozems of Western Siberia as Influenced by Human Impact
Bibliographic record
Abstract
As it is known, the formation of soil humus as well as soil formation is controlled by Dokuchaev’s five soil-forming factors, i.e by climate, vegetation, relief, soil-forming rock and age of the landscape. In connection with fact that the soil has been subjected by heavy human impact during latest one and a half century, it became necessary to take into account the sixth factor, i.e. the anthropogenic one. As for Western Siberia, despite the relatively young farming (mean age of ploughland is about 80-90 years) as compared to other parts of the planet, appreciable humus losses have been progressed from the soils. It is especially observed in the soils of chernozem type widely spread in the forest steppe belt. Along with humus losses, the changes of quality of soil organic matter and structure of its principal constituents are in progress. The paper in question deals with the change of the nature of the most sustainable constituent of soil humus such as humic acids (HA). The study has been performed by the example of leached chernozems (Luvic Chernozem) which are widely spread in Western Siberia and used in long-term dry farming as well as under influence of irrigation.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".