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Record W4379232694 · doi:10.3390/agronomy13061548

Feasibility of Tea/Tree Intercropping Plantations on Soil Ecological Service Function in China

2023· article· en· W4379232694 on OpenAlexaff
Yutong Feng, Trey Sunderland

Bibliographic record

VenueAgronomy · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgroforestry and silvopastoral systems
Canadian institutionsUniversity of British Columbia
FundersChina Three Gorges Corporation
KeywordsIntercroppingMonocroppingEcosystem servicesAgroforestryEnvironmental scienceService (business)ChinaEcosystemAgronomyBusinessGeographyAgricultureEcologyCroppingBiology

Abstract

fetched live from OpenAlex

In order to explore whether tea/tree intercropping plantations have positive effects on soil ecosystem services functions, the possible effects of intercropping cultivation of 151 different tea and other species’ intercropping setups were summarized and analyzed in terms of three aspects of soil ecological service functions (supply services, support services, and regulating services). An ArcGIS map was plotted to show the distribution of existing intercropping plantations in China up to June 2021. Furthermore, it was concluded that the benefits of intercropping tea plantations exceeded those of monocropping tea plantations in terms of soil ecosystem service functions, such as water retention capacity, mineral contents, effects on energy transformation, and regulating environmental conditions. Intercropping tea plantations were more sustainable than regular tea plantations because of the different degrees of variability and benefits in all three aspects mentioned above. However, tea and tree intercropping plantations often require careful planning and preliminary experimentation to determine the type of intercropping that will have positive impacts, especially in the long term.

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 score0.051
Threshold uncertainty score0.387

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 studies0.0000.000
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 head0.046
GPT teacher head0.248
Teacher spread0.202 · 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

Citations18
Published2023
Admission routes1
Has abstractyes

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