Mine Planning for Overburden Target Achievement in First Quarter of 2024 at Pit 3 PT Bina Sarana Sukses PT Tanjung Alam Jaya Jobsite Banjar, South Kalimantan
Bibliographic record
Abstract
Abstract PT Tanjung Alam Jaya plans to mine Seam A, Seam B, and Seam C in Pit 3 in near future which has dense vegetation and thick overburden material with a dip of 23°-25°. The steep slope of the coal seam results in a high Stripping Ratio (SR). The study was conducted using quantitative method with primary data collection through field observation and secondary data from PT Bina Sarana Sukses and other sources. The data is processed and analyzed to determine the best mine plan design. The mining direction for the first quarter of 2024 will start from the north area and widen to the south, following the strike of the coal seam. The design for the first quarter of 2024 Pit 3 is divided into three monthly sequence designs with a total overburden capacity of 2,264,048.21 BCM and 103,555.4 tons of coal, with an SR of 21.86 in accordance with the provisions of 115% of the production capacity of the determined by the company. The current study concludes the need of loaders and haulers, with a total of 3 loaders and 14 haulers for overburden removal target ranged from 621,160.89 BCM to 685,537.27 BCM for three monthly sequences.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".