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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

2025· article· en· W4407722807 on OpenAlexaboutno aff
A Thomas William, Dian Eka Aryanti, Mesias Citra Dewi, Novan Bagaskara

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2025
Typearticle
Languageen
FieldEngineering
TopicMining Techniques and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)OverburdenMining engineeringBusinessOperations managementEngineeringArchaeologyGeography

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.198
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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