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Record W2973212524 · doi:10.30970/vgg.2017.51.8851

Grey forest soils in the different classification systems

2017· article· en· W2973212524 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueVisnyk of the Lviv University Series Geography · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLand Use and Management
Canadian institutionsnot available
Fundersnot available
KeywordsSoil waterUSDA soil taxonomyGeographySoil classificationUnified Soil Classification SystemGrey literatureSoil surveyForestrySoil scienceEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.239
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it