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Record W4409922785 · doi:10.31004/cdj.v6i1.42056

PEMBANGUNAN SCREEN HOUSE MODREN UNTUK PENINGKATAN PRODUKTIVITAS HOLTIKULTURA SAYURAN DI KABUPATEN MUKO-MUKO, BENGKULU

2025· article· id· W4409922785 on OpenAlexaff
Pitriyani Pitriyani, Tri Astuti

Bibliographic record

VenueCommunity Development Journal Jurnal Pengabdian Masyarakat · 2025
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicPlant Growth and Agriculture Techniques
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Kebutuhan sayuran di Kabupaten Muko-Muko yang harus dikonsumsi sebagai sumber serat dan vitamin oleh masyarakat, sebagian besar masih dipasok dari wilayah luar kabupaten. Oleh karena itu, diperlukan sebuah model budidaya sayuran yang lebih ramah lingkungan dan aman bagi kesehatan masyarakat. Pendekatan ini bertujuan untuk mengurangi residu pestisida dalam sayuran, menjaga ketersediaan pasokan sayuran, serta menjamin kualitasnya demi kesehatan masyarakat. Sebagai langkah strategis, Pemerintah Daerah melalui Dinas Pertanian Kabupaten Muko-Muko berupaya mengembangkan sistem budidaya modern dengan menerapkan teknologi inovatif berupa pembangunan screen house, yang merupakan teknologi smart farming pada budidaya hortikultura yang menggunakan bahan-bahan inovasi teknologi canggih dengan struktur pelindung berupa rangka dan jaring, layer UV untuk melindungi tanaman dari serangan hama, penyakit, serta kondisi cuaca ekstrem seperti hujan deras dan angin kencang, sistem irigasi otomatis, sensor suhu dan kelembapan, shading net yang dapat dikendalikan. Teknologi ini memungkinkan pengelolaan lingkungan mikro secara optimal dengan memanfaatkan sistem Internet of Things (IoT), yang merupakan penerapan smart agriculture.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0080.001
Scholarly communication0.0020.001
Open science0.0050.002
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.240
Teacher spread0.215 · 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; both teacher heads agree on what is shown here.

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
Published2025
Admission routes1
Has abstractyes

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