Bibliographic record
Abstract
According to various data, the area of grey forest soils in the world is 94–120.2 million ha, in Ukraine – 4.7–5.5 million ha (about 9 % of the country’s territory). The diversity of conditions for the formation of these soils, discussions about their genesis are the causes of different approaches to the classification of grey forest soils. The history of the classification of grey forest soils is analysed; the most common variants of their classification in Ukraine are presented. Seeking to find approximate equivalents, an attempt to find grey forest soils in the classification systems of different countries (Russia, Moldova, Bulgaria, Romania, Czech Republic, Poland, USA, Canada), as well as in the legend of the FAO-UNESCO map and the WRB has been made. To establish exact analogues of soils practically it is impossible due to different principles of classification’s construction. Modern soil classifications of different countries are as close as possible to WRB and “Soil Taxonomy”. The following names of grey forest soils are identified as the most grounded: light grey forest, grey forest and dark grey podzolic. The following equivalents of the WRB nomenclature (2014) for sub-types of grey forest soils are offered: light grey forest – Albic Luvisols, grey forest – Haplic Luvisols, dark grey podzolic – Luvic Greyzemic Phaeozems. To the names of analogues of these soils with gleyic properties, the qualifier “Gleyic” should be added before the name of the reference soil group. The urgent task for soil scientists of Ukraine is to create a new soil classification that would preserve the acquisitions of genetic soil science but took into account the world trends: the allocation of diagnostic horizons and features that have clearly defined quantitative boundaries. In the new classification, it is proposed to combine the light grey and grey forest soils by a separate group, dark grey podzolic soils to be grouped together in a group with podzolic chernozems. The need for such selection is confirmed by the study of the dark grey soils position in different classification systems of the world, most of which these soils are in the chernozemic type group (Mollisols, Phaeozems and Chernozems). Key words: classification, grey forest soils, Greyzems, Luvisols, Mollisols, Phaeozems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".