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Record W4389444267 · doi:10.37339/jurpikat.v4i3.1456

Pembuatan Pupuk Kompos dari Kotoran Sapi di Desa Mekar Jaya

2023· article· id· W4389444267 on OpenAlex
Yunandra Yunandra, Muhammad Aryo Armanda, Daniel Ginting Suka, Anwary Mahsa, Wahyu Pratama Pratama, Reztiana Reztiana, Dwitya Nurrahma, Ika Nadia Sari, Dhea Ananda, Anastasya Anastasya, Yunita Yunita

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJURPIKAT (Jurnal Pengabdian Kepada Masyarakat) · 2023
Typearticle
Languageid
FieldEnvironmental Science
TopicWaste Management and Recycling
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Limbah kotoran sapi sering menjadi masalah yang berdampak pada pencemaran lingkungan termasuk di Desa Mekar Jaya. Kecamatan Kampar Kiri Tengah, Kabupaten Kampar. Pengabdian ini ditujukan untuk memanfaatan limbah kotoran sapi agar mencegah pencemaran lingkungan dan menjadi tambahan ekonomi bagi peternak di Desa Mekar Jaya. Metode pelaksanaan kegiatan dilakukan dengan cara sosialisasi dan praktik langsung di lapangan dalam pengelolaan limbah kotoran sapi. Hasil kegiatan pengabdian masyarakat pada sosialisasi ini menambah wawasan masyarakat akan pentingnya pengolahan limbah kotoran sapi menjadi pupuk agar tidak mencemari lingkungan. Pelaksanaan kegiatan tersebut berlanjut pada praktik pembuatan pupuk kompos kotoran sapi. Proses nerjalannya kegiatan pembuatan pupuk organik dilakukan dengan hasil yang baik dan sesuai dengan yang diharapkan.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.051

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 head0.019
GPT teacher head0.241
Teacher spread0.222 · 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