Study of Carbon Value of the Allotment of Former Coal Mining Land of PT Samantaka Batubara for Sustainable Mining Environment
Bibliographic record
Abstract
Sustainable environment is a hope for the sustainability of a civilization, because environmental damage can destroy civilization. Mining commodities needed by humans to build civilization and the fulfillment of the necessities of life such as houses, high rise buildings, motor vehicles, mobile phones, electronic equipment, home appliances, office equipment, and others. Mining activities are conducted to obtain mining commodities. Mining companies during the life of the mine are obliged to keep the mining environment sustainable, and entirely entitled to determine its former mining land. Revegetation activities on former coal mines can provide external benefits of carbon values. Research conducted by survey with quantitative method aims to provide an economic assessment of the carbon value of former coal mine land of PT Samantaka Batubara for rubber plantations. The research finds that the carbon value of former mining land of PT Samantaka Batubara for rubber plantation can keep the mining environment sustainable. The economic valuations undertaken to determine the value of carbon use the equations found in this study developed from previous studies. The results of the study found the value of carbon benefits on mining land of PT Samantaka coal worth IDR 1,014,329,829, - or USD 75,770 for the range of restoration of ex-mining land in 2017-2022 PV 2017. The results are expected to be useful and can be used by stakeholders, academics, researchers, practitioners and associations of mining, and the environment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".