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Record W4377840245 · doi:10.29303/wicara.v1i3.2447

PEMANFAATAN AQUAPONIK SEBAGAI TEKNOLOGI BUDIDAYA IKAN NILA DAN SAYURAN YANG MENDUKUNG PERTANIAN BERKELANJUTAN DI DESA KAYANGAN, KECAMATAN KAYANGAN, KABUPATEN LOMBOK UTARA

2023· article· en· W4377840245 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
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

VenueJurnal Wicara Desa · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal Management and Development
Canadian institutionsnot available
FundersUniversitas Gadjah MadaMcGill University
KeywordsAquaponicsSowingFish <Actinopterygii>NutrientManureChicken manureHorticultureBiologyEnvironmental scienceAgricultural scienceAgronomyFisheryAquacultureEcology

Abstract

fetched live from OpenAlex

This introduction to aquaponic planting techniques aims to provide examples of the application of advanced and sustainable agricultural technology to the people in Kayangan village, Kayangan sub-district, North Lombok district (KLU). This activity was carried out from December 2022 to February 2023 at the Bagek Kembar hamlet, Kayangan. The fish used were 60 days old fish seeds with a size of 10 cm x 5 cm which were reared in a 4x3 m tarpaulin container. The plant growth media used is in the form of used foam taken from one of the residents' houses with a size of 5 cm. Placement of the planting media uses used plastic cups and used bottles as containers for placing plastic cups. The vegetables used in making this aquaponics are mustard greens, lettuce and pakcoy. The nutrients used to support plant growth are in the form of fish manure and some additional organic nutrients which are made independently using organic waste from the kitchen. The results of using aquaponic technology as a cultivation technology show that the plants grow but the leaves of the plants turn yellow and the fish in the pond can grow large.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.004

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 head0.014
GPT teacher head0.231
Teacher spread0.217 · 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