Evaluating the potential source of contamination from sulfide minerals in major rocks in South Korea
Bibliographic record
Abstract
The utilization of surrounding rocks is required in human living areas, and these development activities create large cut slopes and generate large amounts of cut rocks as construction materials. If these development areas are strata containing sulfide minerals (pyrite, etc.), contamination may occur, causing environmental pollution problems in the development site and surrounding areas. Several methods have been studied for the preliminary identification of potentially contaminated rocks, including Acid Base Accounting (ABA), Modified ABA procedures, Carbonate Neutralization Potential determinations, Humidity cell tests, Column tests, Batch reactor (Shake flask) tests, and Field tests (Orava, 1997; USEPA and Hardrock Mining, 2003). Studies on rock samples have resulted in most of the samples being classified as Non-Acid Forming (NAF), with some samples containing sulfide minerals (such as pyrite) being classified as Potentially Acid Forming (PAF). It can be expected that future development of these rocky areas may affect the surrounding environment or rock utilization. Therefore, these rock areas are considered to be in need of management. It would be desirable to investigate the occurrence of pollution sources caused by mineral sulfides in advance and take appropriate countermeasures. It is expected to reduce the economic losses that may occur in the future, and it is judged that the pollution problem of the surrounding environment can be further reduced.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".