Application of orientation biogeochemical exploration method in the vicinity of Ildong Fe-Pb-Zn skarn deposits in Korea
Bibliographic record
Abstract
Orientation biogeochemical exploration was applied in the vicinity of Ildong Fe-Pb-Zn skarn deposits in Korea. Sampling was conducted along four traverse lines and control areas. A total of 12 rock, 64 soil and 320 plant samples (including three species such as Daimyo oak leaves/branches (Quercus dentata), Ash tree leaves/branches (Fraxinus rhynchophylla Hance) and Japanese red pine leaves (Pinus densiflora Siebold & Zucc.)) were collected and analysed. The content of Cu, Pb, Zn, Mn, Cd, As and Mo in soil from target areas (n = 56) were 2.0–4.5 times higher than those from control areas (n = 8). However, there were no specific contrasts of element content in plant samples (each n = 56) except both for Pb in Q. dentata leaves (0.45–54.93 mg/kg Pb) and branches (0.73–25.89 mg/kg Pb) and Cd in P. densiflora leaves (0.06–4.08 mg/kg Cd). The biological absorption coefficient for each plant sample was low, except for Cd and Mo, which shows 0.214 and 0.149 respectively in P. densiflora. Also, element content in soils and P. densiflora leaves is positively correlated and these geochemical variations of Cd and Mo show similar trends. Therefore, P. densiflora leaves showed the possibility of Cd and Mo indicator in these types of deposits.
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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".