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Record W4310676607 · doi:10.5539/jsd.v16n1p38

Sustainability Assessment of Productive Palm Tree Plantation in the Arid Regions of Urban Landscapes: A Dubai Case Study

2022· article· en· W4310676607 on OpenAlexvenueno aff
Maryam Shourideh, Peiman Kianmehr

Bibliographic record

VenueJournal of Sustainable Development · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDate Palm Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPalmAgroforestryIrrigationProductivitySustainabilityAridPhoenix dactyliferaGeographyArecaceaeForestryEnvironmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

Dubai has imported elegant plants and trees to maintain a green and attractive outdoor atmosphere. However, a substantial proportion of the imported plants are not suitable for the arid climate of United Arab Emirates (UAE) and require intensive irrigation. This poses the potential of replacing all the greenery with date palm trees that are compatible with the region’s climate and require more moderate irrigation. The availability and value of reclaimed irrigation water, the local soil quality, the cost analysis of date palm tree plantation, the productivity of palm trees, the appropriateness of types of palm trees, the nutritional value of dates, the required gardening workforce, maintenance schedule, and its positioning in relation to seasonal business activities are also explored. Dubai has the capacity to accommodate sixteen times the number palm trees it currently has.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.048
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.298
Teacher spread0.273 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2022
Admission routes1
Has abstractyes

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