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Record W4292209137 · doi:10.35138/gp.v3i2.355

POTENSI EMISI GRK DARI SEKTOR PETERNAKAN DESA CIKALONG,KAB. BANDUNG BARAT TAHUN 2016-2021

2021· article· id· W4292209137 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.

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

Bibliographic record

VenueGEOPLANART · 2021
Typearticle
Languageid
FieldEngineering
TopicWetland Management and Conservation
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesForestryGeographyPhilosophy

Abstract

fetched live from OpenAlex

Salah satu sektor yang berkontribusi dalam peningkatan pemanasan global adalah limbah peternakan yang diantaranya berasal dari kotoran hewan. Sumbangan emsinya diantaranya berasal dari gas metana (CH4), dinitrogen oksida (N2O), karbon dioksida (CO2), dan amonia yang dapat menimbulkan hujan asam. Tujuan penelitian adalah untuk mengetahui sumbangan emisi Gas Rumah Kaca (GRK) dari sektor peternakan tahun 2016 sampai 2021 pada tempat penampungan hewan berupa penggemukan sapi perah dan sapi potong di Desa Kecamatan, Cikalong Wetan, Kabupaten Barat. Penelitian ini mengunakan metodenya survei lapangan dan study literatur untuk memperoleh data primer serta data sekunder berupa populasi ternak dan pengelolaan limbahnya. Data diolah dengan mengunakan metoda Tier I dari IPCC. Hasil penelitian menujukkan bahwa Tahun 2016 Desa Cikalong memberikan sumbangan emisi sebesar 2610,55 ton CO2- eq/tahun meningkat hingga 3632,16 ton CO2-eq/tahun pada Tahun 2019 yang didominasi oleh CH4 dari fermentasi enterik

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.007
GPT teacher head0.185
Teacher spread0.178 · 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