Management of Oil Palm’s Residues for Utilization: Reduced Amount of Greenhouse Gas
Bibliographic record
Abstract
As the demand of oil palm outputs in the world market and Thailand has increased, it results in the oil palm‘s residues which need to be utilized. The study aimed to investigate the utilization of oil palm’s residues and analyze the greenhouse gas emission from the utilization of oil palm’s residues. The study reviewed related literature to obtain concepts, theories, research works, policies, and measures related to the utilization of oil palm’s residues and interviewed to relevant scholars and agencies. The greenhouse gas emission on the utilization of oil palm’s residues were calculated and then compared. The study findings revealed the utilization of the residues and the emission of greenhouse gas as follows: cultivation of straw mushroom from empty palm bunch emitted greenhouse gas 323.1264 KgCO2eq /year; use of oil palm fronds as animal feed emitted greenhouse gas 109.674 KgCO2eq /year; use of empty palm bunch to cover soil emitted greenhouse gas in total 109.674 KgCO2eq /year; composting from residues from palm oil extracting plants emitted greenhouse gas 210.346 KgCO2eq /year, compilation of oil palm fronds in heaps revealed no greenhouse gas emission, and composting from palm bunch emitted greenhouse gas 210.346 KgCO2eq /year.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".