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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 OpenAlex
Maryam Shourideh, Peiman Kianmehr

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.

venuePublished in a venue whose home country is Canada.
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

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.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
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