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Record W3184163085 · doi:10.5937/sustfor1265041r

Beech and fir forest resources in the Pešter plain area

2012· article· en· W3184163085 on OpenAlexfundno aff
Mihailo Ratknić, Ljubinko Rakonjac, Tatjana Ratknić, Sonja Braunović

Bibliographic record

VenueSustainable Forestry Collection · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Plant Ecology Studies
Canadian institutionsnot available
FundersMinistarstvo Prosvete, Nauke i Tehnološkog RazvojaScience and Engineering Research BoardPratt and Whitney Canada
KeywordsBeechShrubCambisolBotanyBiologyHorticultureSoil waterEcology

Abstract

fetched live from OpenAlex

According to EUNIS classification, the analysed stands belong to a mixed beech-fir forest type (G4.61). The soils are eutric cambisol, eutric rankers, distric cambisol and luvisol. 65 plants were identified, out of which 6 tree species, 9 shrub species and 50 ground flora species. The ecological indices have the following averages values: humidity from 2.90 to 3.00, soil chemical reaction from 2.71 to 3.15, nutrient matter from 2.55 to 2.83, light from 2.28 to 2.60 and temperature from 2.56 to 3.07. Out of the total number of recorded plants, 29, that is, 46.0% are medicinal, namely; 4 species come under healing class one, 2 come under healing class two, 11 come under healing class three, 6 come under healing class four and 6 come under healing class five. The following fruit tree species were identified: Vaccinium myrtillis, Crataegus monogyna, Fragaria vesca, Sorbus aucuparia, Lonicera nigra, Rubus hirtus, Sorbus austriacus. 24 melliferous plants were recorded in beech and fir forests, out of which 6 woody, 6 shrub and 10 herbaceous plants. The highest number of melliferous plants blossom in May. The beech and fir forest was recorded on 464.09 hectares. The total volume is 161,015 m3 . The trees with a diameter lower than 30 cm account for 51.5%.

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 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 score0.087
Threshold uncertainty score0.513

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 science0.0000.000
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 head0.011
GPT teacher head0.193
Teacher spread0.182 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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