Evaluation of Household Carbon Absorption for Greenhouse Modeling in East Lombok Regency
Bibliographic record
Abstract
Attention and efforts to reduce greenhouse gases including carbon dioxide is increasing, and begun to be socialized at household level.This study aims to calculate total carbon emissions from household activities that use energy, for evaluation the carbon absorption.The research method was a qualitative survey using questionnaires and field observations from 380 residents spread over 7 villages in Selong sub-district, East Lombok Regency, West Nusa Tenggara Province.Complementary data obtained from literature studies regarding the provisions and rules used.The findings show that indirect emissions originating from electricity use dominate with 69% (481.91638ton CO2/year), which shows very high dependency.The general type of settlement was a mixture of residential and economic activities, which easy to find small shops, service kiosks such as laundry, computer and internet rental, grocery, rented and boarding houses that causes high demand for electricity.Electrical energy comes from diesel power plants that still use coal and other fossil fuels in the production process.Evaluation of emission absorption shows unbalance.It is necessary to save energy usage and also make efforts to find and utilize renewable energy sources and designing scenarios to optimize open spaces, both by increasing the number and model themselves.
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".