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Record W4402956561 · doi:10.18280/ijsdp.190925

Assessment of Food Supply Ecosystem Services and Water Supply Ecosystem Services to Optimise Sustainable Land Use Planning in Samin Watershed, Central Java, Indonesia

2024· article· en· W4402956561 on OpenAlexvenueno aff
Rahning Utomowati, Suranto Suranto, Suntoro Suntoro, Chatarina Muryani

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFisheries and Aquaculture Studies
Canadian institutionsnot available
FundersUniversitas Sebelas Maret
KeywordsEcosystem servicesWatershedJavaWater supplyEcosystemEnvironmental resource managementBusinessWater resource managementSustainable developmentEnvironmental scienceLand useEnvironmental planningEcologyEnvironmental engineeringComputer scienceBiology

Abstract

fetched live from OpenAlex

This research aims to analyze ecosystem services providing food and water as a basis for sustainable land use planning in the Samin watershed.This type of research is a descriptive survey.This research describes spatially the ecosystem services of providing food and water in the research area, which is processed using a Geographic Information System (GIS) with output in the form of an ecosystem services map.The research results show that the Samin watershed Ecoregion is mostly (54%) in the form of Fluvio-volcanic Plain Pyroclastic material and the land cover is dominated by irrigated rice fields (43.69%) influencing the high level of food supply ecosystem services in the Samin watershed, so that the majority (59%) provision of ecosystem services including food is very high.Most of the Samin watershed water supply ecosystem services (72%) are in the high category, influenced by ecoregional conditions and land cover of the Samin watershed.The land cover of the Samin watershed is mostly (72.96%) in the form of land cover which functions for water absorption, and the density of the land cover is mostly (49.721%) including very high density.The research results can be used as a reference for the government in determining policies towards sustainable land use.

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)0.001
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 score0.200
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.011
GPT teacher head0.227
Teacher spread0.216 · 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
Published2024
Admission routes1
Has abstractyes

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