POTENSI EMISI GRK DARI SEKTOR PETERNAKAN DESA CIKALONG,KAB. BANDUNG BARAT TAHUN 2016-2021
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".