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Record W4253881366 · doi:10.33772/jpmit.v2i1.12144

Pemanfaatan Lahan Pekarangan Untuk Pertanian dan Perikanan Dalam Menunjang Ketahanan Pangan Rumah Tangga Masyarakat di Kelurahan Bungkutoko Kecamatan Nambo Kota Kendari

2020· article· en· W4253881366 on OpenAlexaff
R. Marsuki Iswandi, La Ode Alwi, Anas Nikoyan, Samsul Alam Fyka

Bibliographic record

VenueJurnal Pengabdian Masyarakat Ilmu Terapan (JPMIT) · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal Management and Development
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsYardAgricultureAquaponicsService (business)Fish <Actinopterygii>Agricultural scienceBusinessAgroforestryGeographyEnvironmental scienceFisheryAquacultureMarketingBiology

Abstract

fetched live from OpenAlex

The problem that occurs at the community service location is the plot of land which is still not optimally utilized to support the availability of household food from agricultural and fishery foods. The purpose of this community service program is to increase public knowledge and awareness of the importance of using yard space in support of household food availability, in addition to practicing how to use simple plot land in the form of aquaponics to meet the availability of vegetable and fish food as well as using patterns of utilization organically. The method used in this activity is counseling, discussion with residents and the practice of making aquaponics as a model of organic yard use. The result of community service that has been done is a new understanding to the community about the importance of managing yard for agriculture and fisheries to support family food security with the availability of organic food sources in the form of vegetables and fish in their own yard. In addition, the community also knew the simple yard utilization model, namely by using the aquaponics system.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0310.003

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 head0.012
GPT teacher head0.200
Teacher spread0.188 · 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
Published2020
Admission routes1
Has abstractyes

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