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Record W2286790762 · doi:10.5539/jas.v8n2p151

Environmental Soil Quality Research as Prediction for Sustainable Orchards Cultivation in Southern Serbia

2016· article· en· W2286790762 on OpenAlexvenueno aff
Jelena Marković, Svetlana Stevović

Bibliographic record

VenueJournal of Agricultural Science · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Land Suitability Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceHumusSoil fertilitySoil qualitySustainable agricultureSoil testNutrientProductivitySoil nutrientsAgronomyAgricultureAgricultural engineeringSoil scienceSoil waterChemistryGeographyEngineering

Abstract

fetched live from OpenAlex

<p>Soil quality is one of the main environmental conditions for successful and sustainable orchards cultivation. The main role of the soil is reflected in its production activities or productivity. Soil fertility implies content available nutrients, such as individual elements, pH and humus. The research of soil quality leads to certain conclusions about which soil is suitable for growing crops. The investigation of soil quality for Pcinja District in southern Serbia is performed, with the goal to complete environmental conditions for cultivation of the most suitable crops. The methods that were used for the analysis of the soil in the laboratory are: chemical and Al-methods and calibration and potentiometric, spectrophotometric, photometric. For potentiometric method pH meter, spectrophotometer classic which is determined by phosphorus and Flame Photometar device that determines potassium are used. The results in this paper show high quality land for sustainable growing fruit crops.</p>

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)0.005
metaresearch head score (Gemma)0.001
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 score0.332
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.022
GPT teacher head0.297
Teacher spread0.274 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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