Holocene Environmental and Anthropogenic Changes of Soils and Vegetation in the Central Russian Upland: The Case Study in the “Belogorie” Natural Reserve
Bibliographic record
Abstract
Several episodes of past afforestation were reconstructed in a grassland area of the Yamskaya Steppe site within the “Belgorie” natural reserve on the Central-Russian Upland. The pedological, palinological, pedoanthracological, and phytolith analyses were applied for studying paleosols buried under artificial and natural mounds, colluvial fan deposits in gullies, and closed depressions on watersheds. The watershed area was covered by the forest vegetation until 6000 years BP, as indicated by palinological spectra in the paleosol of this age. The Bk horizon of the Chernozemic paleosol buried under a burial mound of the Bronze Age (4630 ± 180 years BP) contained Fe-lamellae indicative of the preceded forest phase of soil formation. Micro-depressions within the local watershed contained charcoal-cored iron-manganese concretions with the radiocarbon age varying from 6055 ± 20 to 6155 ± 20 years BP. This age marked a deforestation of the area after large-scale fires. From that time on, the watershed was dominated by the grassland vegetation. The next phase of afforestation was recorded in the beginning of the Subboreal period of Holocene (4600 BP), but the forest appeared to be limited to gullies. Starting with the Subboreal period, the anthropogenic impact on the landscape became apparent.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".